We help companies manage and access the world’s spatial data.
Any size, any slice, any insight.
Delivered in seconds.
We’re building something that hasn’t existed before: a new layer of the internet where the “where” and “when” behind every decision is instantly clear, programmable, and actionable. Our platform removes the complexity that has kept spatial data locked in silos for decades, and replaces it with speed, precision, and control.
We’re a Calgary-based company, early and moving fast, with real customers, real infrastructure, and a clear point of view on where the world is going.
Why BigGeo Exists and Why People Build Here
Most companies are spatially blind. They know what their data says, but not where or when things actually happen. That gap costs real money, creates real risk, and limits what AI can actually do in the physical world.
BigGeo exists to close that gap.
We’re not building another tool. We’re building the rails that connect the planet’s moving data to the systems that run the world. That’s a big problem, and it takes people who care about doing things right, not just fast.
People build here because:
The problem is real and the category is open. We’re not competing for the middle of an existing market, we’re defining a new one. Your work shapes what the category becomes.
Your fingerprints are on the architecture. We’re at the stage where the decisions you make today become the foundation tomorrow. What you ship matters.
We run on clarity, not politics. We move with purpose. No bureaucratic drag, no HiPPO decisions, just a team that agrees on the mission and gets to work.
You’ll grow fast because the problems are hard. Spatial data at scale is a genuinely difficult domain. If you want to be stretched, you’ll be stretched.
We’re building for longevity. We’re not chasing hype cycles. We’re building infrastructure, the kind that compounds in value over time and earns the trust of the companies that depend on it.
The Role
BigGeo is hiring a Spatial Cloud Solutions Architect to help enterprises, partners, and developers design real systems on top of the Spatial Cloud. This role sits at the intersection of platform architecture and real-world implementation. You turn complex spatial data challenges into scalable, production‑grade solutions that organizations can run their business on.
You’ll work directly with customer engineering teams, enterprise architects, developer partners, and our internal product and engineering groups. You’ll help organizations move from fragmented spatial workflows, manual GIS stacks, point‑to‑point pipelines, batch reporting, to unified spatial intelligence systems that power operations, analytics, and AI‑driven decision‑making in real time.
This is a role for engineers and spatial systems practitioners who like building real things with real customers. You’ll shape how the Spatial Cloud is adopted in the field, and that field feedback loop will directly influence what we build next.
Key Responsibilities
Design Spatial Cloud architectures that integrate spatial datasets, compute systems, and downstream applications.
Translate customer and partner requirements into scalable, maintainable spatial system designs.
Develop architecture patterns that hold up under real performance, reliability, and governance demands.
Produce architecture diagrams, design documents, and decision records that engineering teams can execute against.
Customer and Partner Engagement
Work directly with enterprise customers implementing spatial intelligence systems on the Spatial Cloud.
Support developers and partners building products on BigGeo infrastructure, from initial design through production launch.
Provide technical guidance during onboarding, implementation, scaling, and ongoing optimization.
Run technical deep‑dives, workshops, and design sessions with customer architects and engineering leaders.
Platform Integration
Design APIs, data pipelines, and integration workflows that connect spatial data to operational systems.
Ensure solutions use BigGeo infrastructure to deliver high‑performance spatial queries and real‑time insight.
Partner with BigGeo engineering teams to improve platform capabilities based on what you see in the field.
Technical Enablement
Write solution documentation, technical guides, and reference implementations that customers and partners can actually use.
Build reusable solution patterns that accelerate Spatial Cloud adoption across industries and use cases.
Create and maintain sample apps, starter kits, and code examples that shorten time‑to‑first‑value.
Cross‑Functional Collaboration
Work with product teams to translate implementation feedback into platform improvements.
Support go-to‑market teams with technical insight for enterprise engagements, technical evaluations, and partner conversations.
Collaborate with engineering to ensure production reliability of customer deployments.
What You Bring
Required:
5+ years of experience working with geospatial systems, spatial data platforms, or location intelligence infrastructure.
Bachelor’s degree in Computer Science, Geography, or a related field.
Proven experience designing and deploying spatial data pipelines or geospatial applications in production.
Strong working knowledge of cloud infrastructure (AWS, GCP, or Azure), APIs, and distributed systems.
Experience integrating spatial data with enterprise applications, analytics platforms, or AI systems.
Strong technical communication skills, able to guide both customer engineers and internal teams through complex design decisions.
Comfort operating in a startup environment: high ownership, tight cross‑functional collaboration, fast iteration.
Nice to Have:
Hands‑on experience with GIS platforms, geospatial compute engines, or spatial databases (PostGIS, BigQuery GIS, Snowflake spatial, Esri, H3, S2, or similar).
Experience designing real‑time or high‑performance spatial data systems, including streaming spatial pipelines or low‑latency spatial query layers.
Familiarity with developer ecosystems and API‑driven platforms: SDK design, developer experience, API versioning, and documentation.
Experience supporting enterprise implementations of data platforms, including security, governance, and compliance considerations.
Domain experience in logistics, infrastructure, urban systems, energy, telecommunications, financial services, or climate/earth observation.
Experience building with AI or machine learning systems that incorporate spatial data, including retrieval pipelines, spatial context for LLMs, or spatially aware agents.
Success Measures
First 30 days:
Full onboarding to the Spatial Cloud platform, internal architecture, and active customer implementations. Shadow active customer engagements and meet the product, engineering, and go‑to‑market leads you’ll work with most. Produce a first internal architecture review or design write‑up that demonstrates command of the platform.
First 60 days:
Own the solution design for at least one active customer or partner implementation. Publish at least one reusable reference architecture, solution blueprint, or integration pattern adopted internally. Establish a recurring feedback loop with product and engineering based on field observations.
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Shape the future of spatial data at BigGeo as a Spatial Cloud Solutions Architect in Calgary. Your expertise will help enterprises transform their spatial data challenges into scalable solutions.
In this pivotal role, you will design spatial architectures for organizations and guide partners in implementing spatial intelligence systems. You'll engage with customer engineering teams, translating their needs into practical solutions that enhance operations and analytics. Your work will directly influence the evolution of the Spatial Cloud while streamlining fragmented workflows.
Key Responsibilities:
• Design spatial architectures integrating datasets and applications
• Develop scalable, maintainable spatial system designs
• Produce actionable architecture diagrams and documentation
• Support enterprise customers during implementation and scaling
• Design APIs and data workflows for operational systems
Requirements:
• 5+ years with geospatial systems and location intelligence
• Bachelor’s degree in Computer Science, Geography, or similar
• Proven experience with spatial data pipelines
• Knowledge of cloud infrastructure (AWS, GCP, Azure)
• Strong technical communication skills for collaboration
Impact the evolution of spatial technologies at BigGeo in Calgary through innovative architectural designs.
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Full-time Permanent Associate
Posted 14 May 2026
Description
Workingwith AMPS
AMPS is a mining engineering and geology consultancy specialising in operationalsupport, both onsite and remotely. Established in Australia 15 years ago, AMPShas built a strong reputation in the industry and is now expanding rapidlyacross North America.
Working in Canada with AMPS offers the opportunity to broaden your technical andoperational experience across a very different mining environment, workingalongside established North American operations and teams. For Australianengineers, it is a chance to experience a different landscape, climate andculture, while working alongside Canadians, who may teach you about snowmobilesand ice-fishing!
At AMPS, we invest considerable effort in the success of our people throughselection of assignments, pre-deployment training, and career development overa career with AMPS.
Our on-site staff are supported by their team leaders and a network of their peers.When we are with our clients, we are committed to delivering great technicalwork, we communicate clearly, help others, and add value for every client.
Our mission at AMPS is to improve the professional capabilities in the resourcesindustry for positive and lasting change.
Find out more about life at AMPS here: https://www.linkedin.com/company/advanced-mining-production-systems/life/amps/
TheRole
We are currently seeking two Project Engineers to be site-based and focused onday-to-day field execution for a Canadian-based operation. This role is basedout of Calgary, Alberta, (or another accepted province), offering theopportunity to work with top-tier North American mining operations, with the optionto engage with the option to engage with projects in the US or Australiain the future
KeyResponsibilities:
Supporting day-to-day field execution and construction activities across active mining projects,with a focus on raise-boring and underground ventilation works; additional activities may include piping and pumping systems.
Assisting with planning, coordination, and sequencing of work in alignment with the projectschedules.
Preparing and maintaining engineering and project documentation, including scopes ofwork, progress records, technical inputs, and turnover documentation.
Liaising closely with site superintendents, supervisors, and construction contractors toclarify requirements and resolve field issues.
Completing field QA/QC activities as needed throughout the project.
Providing input to progress tracking, cost awareness, and change identification, andescalating issues as required.
Participating in site meetings, inspections, and reviews, and supporting clear communicationof technical decisions.
Ensuring work is conducted in compliance with site safety, environmental, and regulatory requirements, including exercising stop-work authority where required.
Assisting in Drill & Blast and production workflows.
WhyAMPS?
Local presence, global reach: Work for a consultancy with strong roots in Australiawhile being based locally in Canada.
Roster: Work a favourable FIFO roster.
Career flexibility: Potential opportunities to work in Australia or on other internationalprojects as the role evolves.
Professional growth: Access to learning and development programs and technical support from the global AMPS engineering team.
Competitive package: An attractive salary and incentive package, including recognition andreward incentives.
AboutYou
Education: Degree in Mining, Civil, or related engineering discipline; a comparable diploma with increased practical experience will be considered.
Experience: 2–5+ years of underground mine site or heavy industrial project experience,preferably in a construction or execution environment.
Technical skills: Strong understanding of field-based project execution, contractorcoordination, and construction support.
Documentation: Ability to produce and review technical and project documentation to supportexecution and handover.
Safety: Strong safety awareness and experience working under site safety managementsystems.
Software: Experience with Deswik.CAD is desirable.
Communication: Clear written and verbal communication skills suitable for a site-based,multi-disciplinary environment.
You will be required to complete a full medical.
Diversityand Inclusion
We welcome and support all applicants, including those identifying as LGBTIQ+,mature workers, and people from diverse cultural and religious backgrounds.
Take the next step in your career with AMPS.
Company Overview
Advanced Mining Production Systems (AMPS) are industry leaders in technical services optimisations, systems and training with significant experience in operational Underground and Open Pit Engineering and Geology.Here at AMPS, we provide a collaborative and innovative culture that enables our employees to thrive both professionally and personally. We offer flexible working options to suit different lifestyles in order for our employees to maintain a passion for their career and achieve a work-life balance. Together, we are changing the future of mining.
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BigGeo is redefining geospatial intelligence with an AI-ready Discrete Global Grid System (DGGS) that transforms how spatial data is captured, indexed, and monetized. Our platform powers mission-critical decisions across sectors where location intelligence drives outcomes—from large-scale infrastructure projects and environmental planning to logistics and emergency response. We are industry agnostic, unlocking possibilities for organizations that have yet to realize the value a system like ours can deliver.
Backed by Vivid Theory, a venture studio dedicated to building transformative technologies, we're a multidisciplinary, entrepreneurial team built for impact. We work quickly, push boundaries, and expect every team member to be both a thinker and a doer.
The Opportunity
We\'re seeking a Senior Platform Engineer focusing on high-performance backend systems using modern statically compiled languages. This role emphasizes building reliable, secure, and performant infrastructure that powers our product offerings. If you\'re a developer who thrives on creating high-performance, observable systems and isn\'t afraid to dive deep into low-level optimizations while building reliable platform services, we want to hear from you!
Primary Responsibilities
Design and implement efficient, reliable, secure, and observable backend systems
Optimize code for performance and resource utilization
Contribute to architectural decisions for distributed systems and big-data processing
Write and maintain observable, instrumented code that enables effective system monitoring
Lead the development of complex platform features
Design and implement scalable data architectures
Conduct thorough performance testing and optimization
Mentor junior developers, promote and enforce best practices
Lead initiatives to align platform development with business objectives, ensuring that all platform functionalities contribute positively to key outcomes and KPIs
Facilitate a smooth transition of platform features to product teams, supporting seamless integration and effective use within product pipelines
Continuously evaluate and optimize the platform to enhance user experience and deliver measurable business value, supporting overall company growth objectives
Assume full ownership and accountability for strategic technology domains, with the ability to articulate their business value and organizational impact
Drive DevOps practices and automation initiatives
Monitor and analyze technical performance of internal systems
Leverage existing CI/CD pipelines and tooling for efficient deployment workflows
Support deployment and operational excellence
Contribute to infrastructure-as-code initiatives
Requirements
Bachelor\'s degree in Computer Science, Software Engineering, Data Science, or a related field (or equivalent practical experience)
Proficiency in modern statically compiled languages
Strong understanding of immutability principles and their application
Expertise in writing efficient, reliable, and secure code
Proficient with both manual memory management and automatic lifetime management techniques
Strong understanding of computer architecture and efficient utilization of available resources
Strong knowledge of fundamental data structures and algorithms
Understanding of performance trade-offs between algorithmic efficiency, distributed systems coordination, and I/O minimization in big data contexts
Experience with modern observability patterns and practices
Backend Technology Stack Requirements
Core Languages & Frameworks
Experience with modern statically compiled languages (Go, Rust, C++, or similar)
Familiarity with testing frameworks and benchmarking tools
Understanding of dependency management and build systems
Databases & Data Storage
Strong experience with relational databases (PostgreSQL, MySQL)
Proficiency with NoSQL databases (MongoDB, Redis, Cassandra)
Experience with time-series databases (InfluxDB, TimescaleDB, or Prometheus)
Knowledge of database optimization, indexing strategies, and query performance tuning
Experience with connection pooling and database driver optimization
Experience with Apache Kafka, RabbitMQ, or NATS
Understanding of event-driven architectures and pub/sub patterns
Knowledge of message serialization formats (Protocol Buffers, Avro, MessagePack)
APIs & Communication Protocols
Expertise in RESTful API design and implementation
Experience with gRPC and Protocol Buffers
Knowledge of GraphQL is a plus
Understanding of API versioning, rate limiting, and authentication patterns (OAuth2, JWT)
Container & Orchestration
Proficiency with Docker and containerization best practices
Experience with Kubernetes (deployment, scaling, service mesh)
Knowledge of Helm charts and Kubernetes operators
Experience with container registries and image optimization
Hands-on experience with at least one major cloud provider (AWS, GCP, or Azure)
Infrastructure as Code
Experience with Terraform or Pulumi
Knowledge of configuration management tools (Ansible, Chef, or similar)
Experience with GitOps practices (ArgoCD, Flux)
CI/CD & DevOps Tools
Experience working with CI/CD platforms (Jenkins, GitLab CI, GitHub Actions, CircleCI)
Ability to effectively leverage existing CI/CD pipelines and deployment automation
Knowledge of automated testing strategies (unit, integration, e2e)
Familiarity with build processes and deployment workflows
Observability & Monitoring
Experience with Prometheus and Grafana
Proficiency with distributed tracing (Jaeger, Zipkin, or OpenTelemetry)
Knowledge of structured logging practices and tools
Experience with APM tools (DataDog, New Relic, or Elastic APM)
Understanding of SLIs, SLOs, and SLA definitions
Experience with code review processes and branching strategies
Familiarity with monorepo or microservices repository patterns
Nice to Haves
A Master\'s degree or relevant certifications in Distributed Systems, Big Data Processing, or Cloud Computing is a plus
Experience with Rust (with tokio.rs) or Scala (with cats-effect) will be given top priority
Experience with Go (Golang) including concurrency patterns, standard library, and popular frameworks
Experience with any modern statically typed language (C++, Java, Kotlin)
Background in big-data processing architectures (Spark, Flink, Hadoop)
Experience with distributed systems and consensus algorithms (Raft, Paxos)
Experience with high-performance data structures and lock-free programming
Knowledge of geospatial data structures and algorithms (PostGIS, H3, S2 Geometry)
Expertise in optimizing I/O operations and understanding of Linux kernel internals
Familiarity with binary protocols and efficient serialization
Experience with distributed eventing systems (e.g., NATS.io, Pulsar)
Experience with service mesh technologies (Istio, Linkerd, Consul)
Knowledge of caching strategies (Redis, Memcached, CDN optimization)
Experience with load balancing and reverse proxy configuration (Nginx, HAProxy, Envoy)
Familiarity with security best practices and compliance frameworks (SOC 2, GDPR, HIPAA)
Experience with performance profiling tools (pprof, flamegraphs, perf)
Knowledge of WebAssembly (Wasm) and its applications
Contributions to open-source projects or maintaining libraries
Experience with chaos engineering and resilience testing
Passionate about code efficiency, reliability, and security
Proactive in finding ways to improve existing systems
Eager to learn, mentor and teach
Strong problem-solving skills and critical thinking
Excellent communication and teamwork abilities
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We help companies manage and access the world's spatial data. Any size, any slice, any insight. Delivered in seconds.
The Spatial Cloud provides a unified architecture that enables organizations to manage spatial data they own, access spatial data from external sources, and produce decision-ready intelligence in seconds.
By combining Unified Data, Real-Time Compute, and Governed Monetization, BigGeo transforms fragmented spatial datasets into a shared operational layer that powers real-world awareness across industries, infrastructure systems, and AI platforms.
Why BigGeo Exists and Why People Build Here
We start by being clear about what we're building and why it matters. BigGeo is building the Spatial Cloud, a foundational infrastructure for how spatial data is managed, accessed, and used in real time across systems, AI, and organizations.
Joining BigGeo means contributing to technology that is shaping a new category as it takes form. The BigGeo team is AI-enabled, cross-functional, and highly collaborative. We value ownership, clarity, and leveraging AI tools to build incredible momentum. The work moves quickly, expectations are high, and impact is visible because what we build is used in real-world environments.
At BigGeo, you will:
Contribute to systems that influence how spatial data is managed and applied
Leverage cutting edge AI tools so that your work shows up in real, high-impact use cases
Collaborate with a multidisciplinary team solving complex, meaningful problems
Work in an environment where autonomy is trusted, results matter, and AI tools are harnessed to boost creativity, output, and results
If you want to do work with real-world impact and help build foundational technology that changes how organizations understand and use spatial intelligence, BigGeo is the place to build that future.
The Role
The Spatial Cloud runs on a referencing architecture that most systems have never had to think about. BigGeo is building DGGS, Discrete Global Grid System, as a native platform primitive: a unified spatial index that makes any data, at any scale, instantly addressable and composable across systems. This role owns that architecture end to end. You will make the design decisions, navigate the tradeoffs, and build the infrastructure that makes DGGS a first-class citizen in a distributed cloud platform. If you have the instincts to reason about how a referencing layer becomes an infrastructure primitive, and the track record to build distributed spatial systems at scale, this is the hardest, most consequential problem in spatial computing right now.
What You\'ll Do
Design and own the distributed architecture that makes DGGS a native referencing layer across the Spatial Cloud, including data models, query paths, and compute boundaries
Drive system design decisions end to end with full accountability for architectural tradeoffs, not just participation in them
Build and evolve the spatial indexing and referencing infrastructure that enables real-time, cross-scale data access at cloud scale
Define integration patterns that allow external systems, AI agents, and organizational data sources to interoperate through a unified spatial layer
Use AI-assisted development workflows, including Claude and Cursor, to accelerate design iteration, documentation, and system validation
Contribute to the technical direction of Nexus, BigGeo\'s agentic spatial intelligence platform, ensuring the referencing foundation is built to support autonomous, real-time spatial decision systems
Participate in technical interviews and architecture reviews to help raise and maintain the engineering bar as the team grows
What You Bring
Required:
8+ years of software engineering experience with a clear focus on distributed systems design and large-scale data infrastructure
Proven track record of owning end-to-end system architecture decisions in production environments, not just contributing to design but driving it
Deep understanding of spatial data structures, indexing strategies, and the tradeoffs involved in building geospatial systems at scale
Ability to reason about how a referencing or indexing layer functions as a platform primitive, including its implications for query performance, data composability, and system interoperability
Strong written communication and system documentation skills - you can turn complex architectural decisions into shared understanding across technical and non-technical stakeholders
Demonstrated AI literacy and comfort using AI tools such as Claude and Cursor to accelerate engineering workflows, design iteration, and technical documentation
Nice to Have:
Familiarity with DGGS frameworks - this is a strong preference, not a hard requirement; the architectural instincts to learn DGGS quickly matter more than prior exposure
Experience building geospatial or earth observation platforms at cloud scale
Exposure to agentic AI systems, MCP server architecture, or real-time spatial compute
Background in defence, energy, or critical infrastructure domains where persistent spatial awareness or real-time deconfliction is a system requirement
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Elevate your engineering career with BigGeo as a Senior Platform Engineer. Focus on high-performance backend systems in a fast-paced, entrepreneurial environment that's redefining geospatial intelligence.
This senior role at BigGeo centers around developing resilient, secure, and optimized backend systems. You will work with modern statically compiled languages to impact mission-critical decisions across various sectors. Emphasizing low-level optimizations, your efforts will support reliable platform services and enhance user experiences with efficient resource utilization.
Key Responsibilities:
• Design and implement secure, observable backend systems
• Optimize code for performance and scalability
• Lead development of complex platform features
• Mentor junior developers in best practices
• Monitor and analyze system technical performance
Requirements:
• Bachelor's in Computer Science or equivalent experience
• Expertise in statically compiled languages
• Understanding of computer architecture and data structures
• Proficient with relational and NoSQL databases
• Experience with Docker and Kubernetes
Bring your skills in backend development and system optimization to BigGeo's innovative team.
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Drive innovation in geospatial technology with BigGeo as a Senior Engineer. Leverage your expertise in C++ and spatial analysis to build groundbreaking solutions for real-time data.
In this high-impact role, you will shape the future of geospatial data utilization. Your expertise in computational geometry and high-performance computing will directly influence our growth as you design and implement robust production-grade libraries. Collaboration across disciplines is essential, and your work will deliver measurable results in real-world applications.
Key Responsibilities:
• Design geospatial libraries with clean APIs and documentation
• Develop high-performance C++ systems with Python bindings
• Optimize computational geometry algorithms for large-scale data
• Validate complex geometries per OGC standards
• Maintain CI/CD pipelines for geospatial services
Requirements:
• 7+ years C++ development experience (C++14/17/20)
• Proficient in Python with FFI binding experience
• Expertise in computational geometry algorithms
• Strong knowledge of geospatial systems and transformations
• Experience with CI/CD and deployment strategies
Elevate geospatial technology with your engineering skills in a high-accountability culture at BigGeo.
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Become a key player at BigGeo, shaping the future of spatial data infrastructure. We need a Platform Engineer to build high-performance, scalable systems within our innovative Spatial Cloud environment.
As part of our Calgary-based team, you’ll take ownership of the core infrastructure that makes spatial data actionable. This role requires designing and implementing distributed systems while collaborating with engineering and product teams. You will directly influence the reliability and performance of our platform, ensuring it meets the demands of real customers and intense workloads.
Key Responsibilities:
• Design distributed infrastructure for spatial data ingestion and processing
• Operate services handling large datasets and workloads
• Ensure platform performance under real production loads
• Implement monitoring and observability systems
• Build internal tools for enhanced engineering efficiency
Requirements:
• Bachelor’s in Computer Science or related field
• 3-7 years in platform or infrastructure engineering
• Experience with distributed systems in production
• Knowledge of cloud infrastructure and containerized environments
• Proficient in backend programming languages like Go or Python
Shape the technical foundation of BigGeo’s future, focusing on impactful engineering solutions.
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Lead the design of a pioneering spatial architecture with BigGeo. This role demands expertise in spatial data systems, focusing on DGGS as a core architecture across the Spatial Cloud.
As a pivotal team member, you will shape how spatial data is managed at scale. You will leverage AI tools while ensuring accountability in system design decisions and architectural trade-offs. This position emphasizes autonomy and collaboration, impacting real-world applications through innovative geospatial technology.
Key Responsibilities:
• Design and own distributed architecture for DGGS in Spatial Cloud
• Make accountable system design decisions and navigate trade-offs
• Build and evolve spatial indexing and referencing infrastructure
• Define integration patterns for external systems and AI agents
• Use AI-assisted development workflows for accelerated design
Requirements:
• 8+ years in software engineering with distributed systems focus
• Proven track record of end-to-end architecture ownership
• Deep understanding of spatial data structures and trade-offs
• Strong written communication skills for technical documentation
• Demonstrated comfort with AI tools like Claude and Cursor
Shape the future of geospatial intelligence by leading innovative spatial systems development at BigGeo.
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We help companies manage and access the world’s spatial data.
Any size, any slice, any insight.
Delivered in seconds.
We’re building something that hasn’t existed before: a new layer of the internet where the “where” and “when” behind every decision is instantly clear, programmable, and actionable. Our platform removes the complexity that has kept spatial data locked in silos for decades, and replaces it with speed, precision, and control.
We’re a Calgary-based company, early and moving fast, with real customers, real infrastructure, and a clear point of view on where the world is going.
Why BigGeo Exists and Why People Build Here
Most companies are spatially blind. They know what their data says, but not where or when things actually happen. That gap costs real money, creates real risk, and limits what AI can actually do in the physical world.
BigGeo exists to close that gap.
We’re not building another tool. We’re building the rails that connect the planet’s moving data to the systems that run the world. That’s a big problem, and it takes people who care about doing things right, not just fast.
People build here because:
The problem is real and the category is open. We’re not competing for the middle of an existing market. We’re defining a new one. Your work shapes what the category becomes.
Your fingerprints are on the architecture. We’re at the stage where the decisions you make today become the foundation tomorrow. What you ship matters.
We run on clarity, not politics. We move with purpose. No bureaucratic drag, just a team that agrees on the mission and gets to work.
You’ll grow fast because the problems are hard. Spatial data at scale is a genuinely difficult domain. If you want to be stretched, you’ll be stretched.
We’re building for longevity. We’re not chasing hype cycles. We’re building infrastructure, the kind that compounds in value over time and earns the trust of the companies that depend on it.
The Role
BigGeo is hiring a Platform Engineer to build and operate the core infrastructure that powers the Spatial Cloud. This is a high-ownership role for someone who wants their engineering decisions to be felt in production, by real customers, on real workloads, every single day.
You will design, implement, and maintain the distributed systems that let spatial data be ingested, processed, and delivered reliably at scale. Your work ensures the Spatial Cloud operates as durable, high-performance infrastructure that teams, applications, and AI systems can trust to run the decisions that matter.
You will partner closely with engineering, data, and product to keep the platform reliable, scalable, and easy to build on as datasets grow, workloads intensify, and new product capabilities ship. Platform Engineers are the people who turn BigGeo’s architecture into production-grade infrastructure.
This is not a maintenance role. This is a build role. You will own systems end to end, ship meaningful changes quickly, and shape the technical foundation that the rest of the company builds on top of.
Key Responsibilities
Platform Infrastructure
Design and implement scalable, distributed infrastructure that powers the Spatial Cloud across ingestion, storage, compute, and delivery.
Build and operate distributed services that manage large spatial datasets and high-volume compute workloads.
Keep platform systems performant under real production load, not just benchmark load.
Contribute to architecture decisions that shape how the platform scales over the next three to five years.
Reliability and Operations
Implement monitoring, logging, tracing, and observability systems that give engineers real visibility into the platform.
Participate in on-call rotation, incident response, and post-incident reviews that turn outages into permanent fixes.
Maintain high availability and operational stability across services that customers rely on.
Define and uphold SLOs, error budgets, and reliability practices that scale with the team.
Build internal tools, libraries, and platform services that make every engineer at BigGeo faster and safer.
Support the APIs and infrastructure that product and data teams depend on daily.
Design platform primitives that are easy to operate, easy to extend, and hard to misuse.
Performance Optimization
Profile and improve the performance of distributed services, data pipelines, and spatial compute paths.
Identify bottlenecks across the stack: network, compute, storage, and serialization layers.
Ship changes that measurably improve throughput, latency, and cost-to-serve as datasets and usage grow.
Infrastructure Automation
Implement infrastructure-as-code, automated deployment pipelines, and reproducible environments.
Maintain CI/CD systems that enable rapid iteration and safe, reversible releases.
Reduce manual toil through automation so the team’s time goes into building, not babysitting.
Partner with data engineers, product engineers, and spatial compute teams on the systems that span their domains.
Contribute to architectural discussions and platform design reviews with clear, written reasoning.
Help ensure the Spatial Cloud platform supports current product commitments and future product ambition.
What You Bring
Required:
Bachelor’s degree in Computer Science, Software Engineering, or a related field.
3 to 7 years of professional experience in platform engineering, infrastructure engineering, or backend systems.
Demonstrated experience building or operating distributed systems in production, not just in prototypes.
Strong working knowledge of cloud infrastructure (AWS, GCP, or equivalent) and containerized environments (Docker, Kubernetes, or similar).
Strong programming skills in one or more backend languages commonly used for systems work, such as Go, Rust, Java, C++, or Python.
Track record of building reliable systems with proper monitoring, alerting, and observability practices.
Hands-on experience with CI/CD and infrastructure-as-code workflows (Terraform, Pulumi, Helm, or similar).
Ability to reason clearly about trade-offs in a distributed environment: consistency, latency, cost, and operability.
Clear written and verbal communication. You can explain an architectural decision to a teammate and to a skeptical stakeholder.
Nice to Have:
Experience working with geospatial or spatial data systems (PostGIS, H3, S2, GeoParquet, tile servers, or similar).
Experience with high-performance data pipelines or real-time compute systems (streaming, columnar stores, vectorized execution).
Familiarity with distributed data processing frameworks such as Spark, Flink, Ray, or equivalents.
Experience supporting developer platforms, internal developer portals, or paved-road tooling.
Prior experience in early-stage or high-growth engineering environments where scope is broad and priorities move.
Exposure to ML or AI workloads running on shared infrastructure.
Advanced AI Skills
BigGeo is an AI-enabled engineering organization. Every Platform Engineer is expected to use modern AI tools to move faster, think more clearly, and build higher-quality systems. As a Platform Engineer, you will be expected to:
Use AI coding assistants such as Claude Code, Cursor, or Copilot to accelerate implementation, refactoring, and test coverage on real production systems.
Use AI to accelerate debugging and system analysis: reading logs, tracing incidents, diffing configurations, and exploring unfamiliar services.
Use AI to draft and pressure-test technical design docs, runbooks, and post-incident writeups before review.
Build internal automations and agentic workflows that reduce manual operational work across the platform team.
Evaluate AI output critically. Treat it as a fast, capable collaborator whose work still needs engineering judgment before it ships.
Share patterns and workflows with the team. If you find a faster way, codify it so everyone benefits.
Success Measures
First 30 days:
You have a working mental model of the Spatial Cloud platform, its services, and its data flows. You have shipped at least one meaningful change to production through the full CI/CD and on-call flow. You have established working relationships across engineering, data, and product.
First 60 days:
You own at least one platform surface area outright, with visible improvements to reliability, performance, or developer experience. You are contributing to architecture and design reviews with clear written reasoning. You have identified at least one area of toil or fragility and have a credible plan to fix it.
First 90 days and beyond:
You are a trusted operator during incidents and a trusted reviewer on platform changes. Your work measurably improves the reliability, throughput, or cost profile of core Spatial Cloud infrastructure. You are shaping what the platform looks like twelve months from now, not just keeping today’s version running.
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