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