Staff Engineer, Agentic AI
San Francisco, CA | Full-Time | On-site
A fast-growing Series A AI company ($32M backed by Eric Schmidt) is building intelligent automation systems for complex engineering workflows. Their platform connects directly into enterprise engineering software and enables AI agents to execute real-world, multi-step workflows across desktop applications used by Fortune 100 companies.
Backed by leading investors and already working with companies like Tesla, BMW, Meta, and Amazon, they are hiring a Staff Engineer to lead the core agent intelligence layer powering the platform.
The Role
This person will lead the architecture and development of production-grade AI agents capable of executing complex workflows reliably, efficiently, and at scale.
You’ll work directly with leadership and help define how the agent reasons, orchestrates tools, manages context, handles failures, and improves over time. The role combines deep technical ownership, hands-on engineering, evaluation infrastructure, and technical leadership.
This is a highly impactful role focused on real-world agentic AI systems, not research prototypes.
What You’ll Work On
Agent Performance & Evaluation
Own agent task success rate and workflow completion metrics
Build evaluation and benchmarking infrastructure for multi-step AI workflows
Define token budgets, cost efficiency metrics, and reliability standards
Improve agent performance through systematic testing and iteration
Workflow & User Understanding
Work closely with users and domain experts to map real-world workflows
Translate user stories into reproducible evaluation frameworks
Expand workflow coverage across increasingly complex engineering tasks
Technical Leadership
Own core decisions around orchestration, tool use, context management, state handling, and error recovery
Lead and mentor a small team of AI engineers
Collaborate cross-functionally across product, integrations, and customer deployments
Stay hands-on technically while driving architectural direction
Ideal Background
7+ years of software engineering experience
Strong experience building production AI agents or agentic AI systems
Deep understanding of LLM orchestration, tool calling, and evaluation frameworks
Experience building systems that manage multi-step workflows and operate under reliability/cost constraints
Strong Python experience
Experience leading technical direction for small engineering teams
Nice to Have
Experience with desktop automation or systems-level integrations
Exposure to CAD, manufacturing, robotics, or industrial software environments
Familiarity with agent benchmarking/evals
Experience working on enterprise AI deployments
Open-source or published work related to AI systems
Why Join
Work on one of the hardest problems in applied AI
Build production AI agents operating in real enterprise environments
High ownership and direct visibility into technical/product direction
Small, high-talent-density team with strong backing and rapid growth
Opportunity to define the future of AI-driven engineering workflows