DevOps and Site Reliability Engineer We help companies manage and access the world’s spatial data. 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. 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.

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.

We’re not competing for the middle of an existing market. 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. Spatial data at scale is a genuinely difficult domain. We’re building for longevity. We’re building infrastructure, the kind that compounds in value over time and earns the trust of the companies that depend on it.

BigGeo is seeking a DevOps & Site Reliability Engineer to design, automate, secure, and operate the infrastructure that powers the Spatial Cloud. This role is responsible for building reliable cloud infrastructure, deployment systems, observability platforms, security controls, and operational tooling that enable engineering teams to deliver production software with confidence. The role combines DevOps and Site Reliability Engineering responsibilities.

You will build the systems that deliver software to production, and you will own the reliability of what runs there — service level objectives, observability, capacity planning, incident response, and the on-call practice that supports them.

We combine these deliberately: engineers who build delivery systems make better reliability decisions when they also operate what they ship. You will work closely with software engineers, platform engineers, data engineers, and product teams to ensure BigGeo’s systems remain scalable, resilient, secure, and highly available as the platform grows. This role is ideal for someone who enjoys building infrastructure as a product, automating everything possible, and creating systems that allow engineering teams to move faster without sacrificing reliability.

Cloud infrastructure supporting BigGeo production environments Infrastructure-as-Code frameworks and deployment pipelines CI/CD systems supporting engineering delivery workflows Monitoring, logging, alerting, and observability platforms Security automation and compliance controls Reliability engineering practices and operational standards Internal developer platforms and operational tooling Develop and optimize CI/CD pipelines for engineering teams Operate Kubernetes-based production environments Improve system reliability, performance, and fault tolerance Implement monitoring, observability, and alerting strategies Manage cloud networking, security, and access controls Lead incident response, root-cause analysis, and blameless postmortems Perform capacity planning for stateful and resource-intensive workloads Reduce operational toil through automation and elimination of recurring issues Collaborate with engineering teams to improve deployment velocity Evaluate and integrate AI-powered operational and automation tools Reliability is treated as a core engineering responsibility at BigGeo rather than a separate function. This role carries meaningful ownership of it.



Reliability engineering Perform capacity planning for both growth and failure scenarios Drive continuous improvement through postmortems and reliability reviews Production alerting is automated and routed by severity On-call responsibility is currently shared across the engineering team and is being formalized into a structured rotation as the team grows You will participate in that rotation and help define escalation paths, response expectations, and handoff practices On-call scheduling and supporting policies are being established as part of this work Technology and Tools The exact stack will evolve as the platform grows, but experience with many of the following technologies is expected: AWS, Azure, or Google Cloud Platform Infrastructure and Automation AI Tooling Modern AI assistants and development tools AI-supported operational automation AI-enhanced monitoring and troubleshooting workflows 4+ years of experience in DevOps, Site Reliability Engineering, Platform Engineering, or Infrastructure Engineering ~ Strong experience operating cloud infrastructure in production environments ~ Experience building Infrastructure-as-Code solutions ~ Knowledge of CI/CD pipelines and deployment automation ~ Solid Linux systems administration skills ~ Experience with monitoring, logging, and observability platforms ~ Understanding of networking, security, and distributed systems concepts ~ Experience supporting production incident response and troubleshooting ~ Experience participating in an on-call rotation for production systems ~ Experience supporting large-scale data platforms Experience building internal developer platforms Familiarity with high-volume data processing systems Experience implementing reliability engineering practices Knowledge of database operations and performance tuning Experience working within startup or high-growth technology environments Experience integrating AI systems into operational workflows As a DevOps & Site Reliability Engineer, you will build and operate the foundational systems that allow BigGeo to manage and access the world’s spatial data at massive scale.

Your work directly impacts platform reliability, developer productivity, customer experience, and the company’s ability to deliver spatial insights in seconds. BigGeo operates as a highly collaborative, AI-native startup environment. This is an on-site role based in Calgary, Alberta.

Candidates must be located in the Calgary area or willing to relocate. You will work closely with engineering, product, data, and leadership teams while helping establish the operational foundation of a category-defining company. You will have significant influence over how BigGeo scales its platform, operations, and engineering capabilities as we continue defining the Spatial Cloud category.

Success in this role means quickly developing a deep understanding of BigGeo’s production workplace, taking meaningful ownership of platform reliability, and improving the systems that allow engineering teams to deploy and operate the Spatial Cloud safely at scale. Develop a working understanding of BigGeo’s cloud infrastructure, production architecture, Kubernetes environments, networking, deployment systems, and Infrastructure-as-Code. Understand the current CI/CD workflows and how software moves from development through deployment into production.

Review existing monitoring, logging, alerting, and observability coverage for critical services. Understand current production reliability expectations, incident response practices, escalation paths, and the developing on-call model. Shadow production incidents and participate in troubleshooting alongside engineering team members before taking primary on-call responsibility.

Identify initial reliability, security, infrastructure, deployment,



or operational risks and document recommended priorities. Establish working relationships with software, platform, data, and product teams and understand the infrastructure requirements of their workloads. Begin using AI-assisted tools for infrastructure analysis, troubleshooting, automation, documentation, and operational workflows.

You can explain how BigGeo’s production infrastructure operates, how software reaches production, how system health is measured, where the most important operational risks exist, and how you will begin improving reliability and developer operations. Independently own meaningful components of BigGeo’s cloud infrastructure, Kubernetes environments, deployment systems, or observability stack. Deliver at least one material improvement to Infrastructure-as-Code, CI/CD, deployment automation, observability, or operational tooling.

Establish or materially improve SLOs and SLIs for critical production services, creating clearer visibility into reliability and service health. Improve monitoring and alerting so critical production conditions are actionable while unnecessary or low-value alerts are reduced. Participate actively in the on-call rotation with appropriate escalation support and demonstrate effective production troubleshooting and incident response.

Lead or materially contribute to root-cause analysis and blameless postmortems, ensuring recurring issues result in clear corrective actions. Assess capacity requirements for critical stateful or resource-intensive workloads and identify scaling or failure risks. Strengthen infrastructure security, access controls, secrets management, or vulnerability management where gaps are identified.

Use AI-assisted operational workflows to accelerate troubleshooting, infrastructure development, analysis, and automation without compromising reliability or security. You are independently operating important parts of BigGeo’s infrastructure, contributing effectively to production response, and delivering measurable improvements to reliability, automation, observability, and engineering delivery. First 90 Days — Strengthen the Operational Foundation of the Spatial Cloud Own the reliability and operational health of defined production infrastructure and services, with transparent SLOs, monitoring, alerting, and response expectations.

Demonstrate measurable improvement in at least one key operational area such as deployment reliability, deployment velocity, incident frequency, recovery time, alert quality, infrastructure automation, or operational toil. Help establish a structured on-call practice with clear escalation paths, response expectations, handoff practices and supporting documentation. Establish repeatable incident response and postmortem practices that convert production failures into system and process improvements.

Improve infrastructure resilience through capacity planning, fault-tolerance improvements, recovery planning or elimination of identified single points of failure. Deliver reusable infrastructure automation or internal developer tooling that allows engineering teams to deploy and operate services with less manual intervention. Identify cloud cost or resource-efficiency opportunities and implement practical improvements without compromising reliability or performance.

Establish clear operational documentation and runbooks for critical infrastructure, deployment, incident, and recovery workflows. Contribute informed recommendations to platform architecture and infrastructure strategy based on direct production experience. Demonstrate that infrastructure improvements are creating leverage across the engineering organization by making production systems easier to deploy, observe, troubleshoot, recover and scale.

You are operating as a trusted owner of BigGeo’s production reliability. Engineering teams can ship with greater confidence, critical systems are more observable and resilient, operational practices are becoming repeatable, and infrastructure is better prepared to support the continued scale of the Spatial Cloud. #

📌 Un(e ingénieur DevOps - Site Reliability Engineer (Calgary)
🏢 BigGeo
📍 Calgary