DevOps / Platform Engineering Tech Lead

We’re looking for ahands-on DevOps / Platform Engineering Tech Leadwho 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 enjoysbuilding platforms, defining engineering standards, solving complex problems, and helping development teams become more autonomous and efficient.

• Develop our internaldeveloper platform, including self-service capabilities, golden paths, and repository templates, withGitHub as the center of our engineering ecosystem
• Own the administration and support themigration to GitHubacross the organization
• Design and maintainCI/CD with GitHub Actions, including reusable workflows, self-hosted runners, security policies, and secrets management
• Build and maintainInfrastructure as Code with Terraform, including reusable modules, versioning, state management, multi-environment setups, and Policy as Code
• Build and operate theAI model access layer, including gateways, routing, rate limits, and usage observability
• DriveAI cost modeling and optimization, covering input/output pricing, prompt caching, Batch APIs, model selection, and unit economics per feature/user
• EstablishAI cost reportingfor the business, including showback/chargeback, budgets, and alerts
• Work with multiple engineering teams to define and promotebest practices, reusable patterns, and engineering standards
• Mentor engineers and act as a technical partner forarchitects and product teams
• Take ownership of initiatives end-to-end and make sure solutions are actually adopted across the organization

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

• Experience withMicrosoft Azure
• Experience withJenkins
• Experience working withenterprise-scale environments
• Experience building internal developer platforms or platform engineering capabilities