DevOps / Platform Engineering Tech Lead

We’re looking for a hands-on DevOps / Platform Engineering Tech Lead who is not afraid to take ownership, drive change, and work across multiple engineering teams. This is a role for someone who can go beyond “keeping things running” — someone who enjoys building platforms, defining engineering standards, solving complex problems, and helping development teams become more autonomous and efficient. What you’ll do Develop our internal developer platform, including self-service capabilities, golden paths, and repository templates, with GitHub as the center of our engineering ecosystemOwn the administration and support the migration to GitHub across the organizationDesign and maintain CI/CD with GitHub Actions, including reusable workflows, self-hosted runners, security policies, and secrets managementBuild and maintain Infrastructure as Code with Terraform, including reusable modules, versioning, state management, multi-environment setups, and Policy as CodeBuild and operate the AI model access layer, including gateways, routing, rate limits, and usage observabilityDrive AI cost modeling and optimization, covering input/output pricing, prompt caching, Batch APIs, model selection, and unit economics per feature/userEstablish AI cost reporting for the business, including showback/chargeback, budgets, and alertsWork with multiple engineering teams to define and promote best practices, reusable patterns, and engineering standardsMentor engineers and act as a technical partner for architects and product teamsTake ownership of initiatives end-to-end and make sure solutions are actually adopted across the organization What we’re looking for 5+ years of experience in DevOps, SRE, or Platform Engineering, including experience as a Tech Lead or team leadStrong knowledge of GitHub at organizational/enterprise scale, including GitHub Actions, GitHub Enterprise, permissions, governance, and GitHub Advanced SecurityProduction-level Terraform experience — building reusable modules, refactoring state, and managing multiple environmentsHands-on experience with AI model APIs and tooling, such as Anthropic, OpenAI, AWS Bedrock, Google Vertex AI, or similarGood understanding of AI cost models: tokens, context windows, caching, pricing tiers, GPU vs. API costs, and quality/cost/latency trade-offsExperience with Kubernetes, containerization, and cloud platforms such as AWS, GCP, or AzureAbility to communicate about technology and costs with both engineers and finance/business stakeholdersStrong ownership mindset — you take responsibility, make decisions, and drive things to completionAbility to work effectively with a large number of engineering teams, understand their needs, and turn them into scalable platform solutions and practical best practicesStrong communication and collaboration skills, with the ability to influence teams without relying solely on formal authorityNice to have Experience with Microsoft AzureExperience with JenkinsExperience working with enterprise-scale environmentsExperience building internal developer platforms or platform engineering capabilities What we value We’re looking for someone who is pragmatic, proactive, and technically strong. Someone who doesn’t wait for requirements to be handed over, but can identify opportunities, propose solutions, bring people together, and take ownership from idea → implementation → adoption. You’ll have a real opportunity to influence how engineering teams work, how infrastructure is delivered, and how we build and scale our AI capabilities in a secure, observable, and cost-efficient way.