Senior Engineering Manager (AI Developer Experience)

Role Overview

Join Temporal Technologies as a Senior Engineering Manager (AI Developer Experience). You will lead a team that empowers builders by delivering a standardized ecosystem of core engineering and AI tools, partnering across the company to accelerate safe, effective AI adoption.

Key Missions

• Set direction for AI-assisted development (end-to-end):
  • Define an engineering-wide approach for safe, effective AI-assisted workflows (tooling standards, rollout strategy, adoption).
• Build frictionless paved paths:
  • Identify and remove sources of friction in developer workflows.
  • Deliver a small set of deeply reliable, well-supported developer “paved roads” rather than many bespoke solutions.
• Drive governance and cost management for AI tooling:
  • Implement usage measurement, guardrails, and optimization.
  • Use clear metrics/frameworks (e.g., DORA/SPACE) to connect improvements to business outcomes.
• Own strategy and execution for internal AI systems and act as an early adopter of the company’s AI products.

Responsibilities / What You’ll Do

• Partner with teams across the company to accelerate AI adoption.
• Influence and coordinate across boundaries without direct ownership.
• Engage deeply in technical discussions around system design, safety guardrails, operational readiness, and tradeoffs.
• Create environments where engineers can grow and ship high-quality systems.
• Translate ambiguous developer needs into clear guidance, systems, and measurement.

Profile / Requirements

• Proven track record driving adoption of new workflows/platforms across an engineering organization.
• Strong coaching and feedback skills; bias toward action and impact.
• Experience leading teams focused on developer productivity (DevEx), internal platforms, or engineering tooling.
• Ability to standardize without blocking innovation (know when to adopt vs. build).
• Experience evaluating and deploying AI coding tools, developer assistants, and/or LLM-based workflows/agents.
• Comfort with modern developer workflows and the systems that support them.
• Strong software engineering background (backend, platform, or developer tools).
• Experience prioritizing and communicating based on measurable impact.
• Strong empathy for builders, including non-traditional developers.
• Experience building measurement systems for tooling outcomes (e.g., adoption, reliability, cycle time, cost-to-serve, AI spend).

Nice-to-Haves

• Familiarity with governance and operational practices for AI systems, including safety and cost controls.
• Experience using DORA/SPACE-like metrics frameworks for tooling outcomes.