Senior Cloud & DevOps Engineer

3LC.AI is hiring a Senior Cloud & DevOps Engineer to own how its AI data platform is built, shipped, and operated across major cloud providers and customer environments. The role leads multi-cloud infrastructure, software delivery, marketplace distribution, reliability, and engineering practices.

Responsibilities:

• Design, build, and operate 3LC's infrastructure across AWS, Azure, and Google Cloud — networking, compute, storage, identity, and cost
• Define infrastructure as code (Terraform or equivalent) so environments are reproducible across all three clouds and across customer accounts
• Architect for security, reliability, and the realities of deploying a data-heavy ML application into customers' own cloud accounts and private environments
• Own CI/CD end to end — primarily on Azure DevOps — for build, test, packaging, and release, including gated pull-request workflows and quality gates
• Containerize and orchestrate our services and their data stores (including MongoDB) with Docker and Kubernetes, packaged and released with Helm
• Own the installation and upgrade experience for customer-hosted deployments, and be the senior technical escalation point when a customer deployment gets hard
• Automate everything that should be automated, using Python, YAML, and Git-based workflows
• Create and maintain 3LC's listings on the AWS, Azure, and Google Cloud marketplaces — packaging, metering, entitlements, and updates
• Work with product and go-to-market so each cloud's procurement path is smooth for customers
• Stand up monitoring, logging, and alerting so we catch problems before customers do
• Own incident response and post-incident learning (no on-call rotation today)
• Drive down toil and technical debt — make the slow, manual, and fragile parts of our build and deployment fast and boring
• Set standards for code review, testing, release management, and documentation across the engineering team
• Partner closely with our ML and application engineers on architecture decisions that affect how the platform is deployed and scaled
• Mentor others and help shape the team as we grow

Requirements:

• 10+ years of professional software engineering, with substantial hands-on ownership of build, release, and deployment of production software
• Experience developing and deploying a web-based or ML application on at least one major cloud (AWS, Azure, or Google Cloud)
• Production experience with Kubernetes and Docker
• CI/CD pipeline ownership, with hands-on Azure DevOps (or TFS/VSTS) and/or Jenkins experience, and deep fluency with Git
• Strong Linux skills and strong programming ability in Python; comfortable reading and working across TypeScript, C++, or other languages in a polyglot codebase
• Full-lifecycle experience: requirements, design, implementation, testing, packaging, installation, and customer support
• A security-first, quality-first mindset — test-driven development, code review, and a strong sense of ownership for reliability, cost, and maintainability
• Helm-based packaging is a plus
• ideally more than one
• Experience delivering software into customers' own cloud or on-prem environments (BYOC / self-hosted delivery)
• Experience with MongoDB or other data stores running on Kubernetes
• Infrastructure as code with Terraform, Pulumi, or similar; configuration management with Puppet or Ansible
• Experience publishing and maintaining cloud marketplace listings (AWS, Azure, or GCP)
• Experience with AWS SageMaker, Azure ML, or Google Vertex AI; background in GPU workloads or data-intensive systems
• Experience with large-scale source control migrations, cross-platform builds, software licensing, or static analysis tooling
• Familiarity with GitHub Actions, ArgoCD, or other modern delivery tooling