DevOps / Platform Engineering Tech Lead

Quick Facts

Role: DevOps / Platform Engineering Tech Lead. Focus: Hands-on platform engineering and developer enablement centered on GitHub and AI access/cost control.

Description

We’re looking for a hands-on DevOps / Platform Engineering Tech Lead who takes ownership, drives change, and works across multiple engineering teams. This role goes beyond keeping systems running—building platforms, defining engineering standards, solving complex problems, and making development teams more autonomous and efficient.

What you’ll do

• Develop the internal developer platform: self-service capabilities, golden paths, and repository templates, with GitHub as the center of the engineering ecosystem
• Own administration and support the migration to GitHub across the organization
• Design and maintain CI/CD with GitHub Actions: reusable workflows, self-hosted runners, security policies, and secrets management
• Build and maintain Infrastructure as Code with Terraform: reusable modules, versioning, state management, multi-environment setups, and Policy as Code
• Build and operate the AI model access layer: gateways, routing, rate limits, and usage observability
• Drive AI cost modeling and optimization: input/output pricing, prompt caching, Batch APIs, model selection, and unit economics per feature/user
• Establish AI cost reporting: showback/chargeback, budgets, and alerts
• Work with multiple engineering teams to define and promote best practices, reusable patterns, and engineering standards
• Mentor engineers and act as a technical partner for architects and product teams
• Take ownership of initiatives end-to-end and ensure solutions are adopted across the organization

Requirements

• 5+ years of experience in DevOps, SRE, or Platform Engineering, including experience as a Tech Lead or team lead
• Strong knowledge of GitHub at organizational/enterprise scale, including GitHub Actions, GitHub Enterprise, permissions, governance, and GitHub Advanced Security
• Production-level Terraform experience: building reusable modules, refactoring state, and managing multiple environments
• Hands-on experience with AI model APIs and tooling such as Anthropic, OpenAI, AWS Bedrock, Google Vertex AI, or similar
• Good understanding of AI cost models: tokens, context windows, caching, pricing tiers, GPU vs. API costs, and quality/cost/latency trade-offs
• Experience with Kubernetes, containerization, and cloud platforms such as AWS, GCP, or Azure
• Ability to communicate about technology and costs with both engineers and finance/business stakeholders
• Strong ownership mindset: take responsibility, make decisions, and drive things to completion
• Ability to work with a large number of engineering teams, understand their needs, and turn them into scalable platform solutions and practical best practices
• Strong communication and collaboration skills, ability to influence teams without relying solely on formal authority

Benefits

• Real opportunity to influence how engineering teams work, how infrastructure is delivered, and how AI capabilities are built and scaled in a secure, observable, and cost-efficient way
• Chance to take ownership from idea → implementation → adoption