Senior Technical Leader — Agentic AI (Engineering Tools)
Job Summary
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 products real-world value to enterprise customers.
What youll 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.
What were 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 (36 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.
Required Skills:
Python LLM agents tool calling agentic AI evaluation/benchmarking desktop automation COM CAD/CAE/PLM model routing context management observability technical leadership
Required Education:
Bachelors degree from an accredited college or university is preferred but not required.