LEAD CLOUD RELIABILITY & INFRASTRUCTURE

About BigGeo

BigGeo is the Spatial Cloud.

We help companies manage and access the world's spatial data.

Any size, any slice, any insight.

Delivered in seconds.

BigGeo is defining a new infrastructure category for how spatial and temporal data is organized, accessed, computed, and used across systems, organizations, and AI.

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 don't start by asking why you'd be a good fit for us. 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.

BigGeo is the Spatial Cloud.

We help companies manage and access the world's spatial data, any size, any slice, any insight, delivered in seconds.

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

This is the infrastructure owner for the Spatial Cloud, the person who keeps BigGeo's multi-cloud, multi-region systems at 99.99% uptime while building the agentic operations layer that makes that standard achievable without burning out a team. You will combine deep AWS and Azure expertise with hands-on agent orchestration, designing systems that detect issues, diagnose root causes, and remediate autonomously. This is a technical leadership role with real ownership: you'll shape the infrastructure roadmap, mentor a small SRE team, and work directly with the Head of Engineering on hiring. If you think in systems, build for resilience, and want your reliability work to underpin infrastructure that matters at global scale, this role was built for you.

What You'll Do

• Own multi-cloud infrastructure across AWS and Azure — architecture, cost optimization, network design, and database operations at production scale
• Design and operate multi-region Kubernetes clusters with full GitOps workflows, Helm-based deployment strategies, and multi-AZ reliability
• Architect for 99.99% uptime — define SLOs, set error budgets, build disaster recovery plans, and validate failover regularly
• Build agentic operations systems using Claude and LLM-driven tooling to automate log analysis, anomaly detection, and infrastructure diagnostics
• Design autonomous remediation workflows — auto-scaling, config validation, canary deployments, rollback triggers, and human escalation paths
• Lead reliability improvements with measurable targets: reduce MTTR by 50%+ within six months, get 3–5 agentic systems into production
• Mentor 1–2 SRE engineers and partner with the Head of Engineering on team structure and hiring decisions

You'll work primarily in Slack, Google Workspace, and Monday, with your infrastructure stack living in AWS, Azure, Terraform, and Kubernetes.

What You Bring

Required:

• 5+ years with AWS at scale — EC2, RDS, Lambda, VPC, IAM, CloudFront, ECS/EKS, S3 — including multi-region architecture and cost optimization
• 3+ years with Azure — Virtual Machines, App Service, Azure SQL, AKS, networking, and Azure cost models
• Production Kubernetes experience in multi-region, multi-AZ environments — pod scheduling, networking, storage, autoscaling, and debugging
• Infrastructure-as-Code proficiency in Terraform, CloudFormation, or Bicep; Python or Go for automation and agent tooling
• Hands-on experience building LLM-driven diagnostic workflows or agentic operations systems, with comfort operating autonomous systems safely
• Strong AI literacy and demonstrated use of AI tools — including Claude or similar — to accelerate infrastructure analysis, automation, and decision-making

Nice to Have:

• Background with geospatial data infrastructure or spatial platforms
• Familiarity with FinOps practices and Reserved Instance/Spot Instance optimization at scale
• Prior experience mentoring SRE or infrastructure engineers toward a leadership track