Senior Technical Leader — Agentic AI (Engineering Tools)

Senior Technical Leader — Agentic AI (Engineering Tools)
San Francisco, CA, on-site · Full-time · No sponsorship

The build: Our client is hiring a senior technical leader to own the core agent intelligence that turns mechanical engineers' intent into reliable, cost-efficient multi-step workflows across desktop engineering tools. This role sits at the intersection of applied agentic AI, user research, and product delivery — and will determine the product's real-world value to enterprise customers.

What you'll do

• Lead development of the core agent intelligence layer that executes multi-step workflows across complex desktop engineering software.
  
• Report to the CTO and serve as technical lead for a small team of AI engineers, a user researcher, and domain expert contractors.
  
• Own the full product loop: define agent capabilities from user stories, build implementations, and benchmark against real workflows.
  
• Drive agent task success rate by defining evaluation frameworks, establishing baselines, and iterating to improve completion metrics.
  
• Set and enforce per-task token budgets and track cost per completed workflow to ensure commercial viability.
  
• Build rigorous, reproducible evaluation infrastructure grounded in validated user stories.
  
• Lead user story mapping and validation through interviews and close collaboration with domain experts.
  
• Translate validated user stories into testable evals and close the loop between research and benchmarking.
  
• Own agent architecture decisions including tool-calling, state management, error recovery, model routing, and context management.
  
• Act as a player-coach: write production code, review designs, unblock the team, raise engineering standards.
  
• Collaborate cross-functionally with integrations, product, and customers during POCs.
  

Requirements

What we're looking for

• 7+ years software engineering, including at least 2 years building agentic LLM-based agents that act in the real world.
  
• Deep experience designing LLM application architectures: model selection, context/window management, retrieval, orchestration patterns.
  
• Proven ability to build evaluation and benchmarking frameworks measuring task completion, cost efficiency, and failure modes.
  
• Technical leadership experience setting direction for small teams (3–6 engineers) and performing meaningful code review.
  
• Strong Python skills and familiarity with LLM tooling (function calling, tool APIs, observability/tracing, evaluation frameworks).
  
• Experience with desktop automation or programmatic control of applications (COM or similar).
  
• Domain experience in mechanical engineering, CAD/CAE, PLM, or adjacent industries.
  
• Understanding of enterprise deployment constraints on locked-down corporate workstations.
  
• Track record contributing to public benchmarks, publications, or open-source agentic AI projects.
  

Logistics: San Francisco, on-site.

No sponsorship. Relocation not available.