What are the responsibilities and job description for the Staff AI Engineer-Agentic position at Stott and May?
Staff Engineer, Agentic AI
đź“Ť 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