Senior Technical Leader — Agentic AI (Engineering Tools)
Fruition Executive Search
- Location
- Onsite (San Francisco, California)
- Compensation
- $160k - $240k/yr
- Employment
- Full-time
- Level
- Senior Level
About the role
The client is seeking a Senior Technical Leader to own the core agent intelligence for desktop engineering tools, turning mechanical engineers' intent into reliable workflows. This role sits at the intersection of applied agentic AI, user research, and product delivery to determine real-world value for enterprise customers.
Skills
Full job details
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.