Senior Engineering Manager, Builder Tools

Temporal · Enterprise · United States · Infrastructure

Leads a team focused on empowering builders with a standardized ecosystem of core engineering and AI tools, acting as internal Forward Deployed Engineers to accelerate AI adoption and providing feedback on internal AI products.

What you'd actually do

  1. Set direction for AI-assisted development, end-to-end: Define the engineering-wide approach for safe, effective AI-assisted workflows (tooling standards, rollout strategy, and adoption).
  2. Build frictionless paved paths: Identify and remove sources of friction in developer workflows; deliver a small set of deeply reliable, well-supported paved roads rather than many bespoke bypasses.
  3. Internal AI platform strategy (build vs. buy): Own strategy and execution for internal agent runtimes and developer-facing AI systems (authoring, review, and automation workflows), including vendor evaluation and integrations.
  4. Governance, cost, and measurement: Drive governance and cost management for AI tooling (usage measurement, guardrails, optimization) using clear metrics and frameworks (e.g., DORA/SPACE) to translate improvements into business outcomes.

Skills

Required

  • Experience leading teams focused on developer productivity, DevEx, internal platforms, or engineering tooling.
  • Track record of driving adoption of new workflows and platforms across an engineering organization.
  • Ability to operate across boundaries and influence without direct ownership; comfort acting as an internal forward-deployed partner.
  • Strong coaching and feedback skills, creating an environment where engineers can grow and ship high-quality systems.
  • Experience evaluating and deploying AI coding tools, developer assistants, and/or LLM-based workflows and agents.
  • Intuition for when to adopt vs. build, and how to standardize without blocking innovation.
  • Strong software engineering background (backend, platform, or developer tools).
  • Familiarity with modern developer workflows and the systems that support them.
  • Ability to engage deeply in technical discussions around system design, safety guardrails, operational readiness, and tradeoffs.
  • Ability to translate ambiguous needs into clear guidance and systems.
  • Strong empathy for builders and their workflows (including non-traditional developers).
  • Experience prioritizing and communicating based on measurable impact, not just qualitative feedback.

Nice to have

  • Experience building measurement systems for tooling outcomes (adoption, reliability, cycle time, cost-to-serve, AI spend).

What the JD emphasized

  • safe, effective AI adoption
  • internal agent runtimes
  • developer-facing AI systems
  • governance
  • cost management
  • guardrails

Other signals

  • AI-assisted development
  • internal agent runtimes
  • developer-facing AI systems