Impress employers and recruiters.
Choose from hundreds of resume examples.
Impress employers and recruiters.
Choose from hundreds of resume examples.
Tailor your resume to this Staff Engineer, Agentic AI role.
Rezi rewrites your resume against Clera's job description. Free.
Tailor your resume to this Staff Engineer, Agentic AI role.
Rezi rewrites your resume against Clera's job description. Free.
Don't guess if your resume is good enough.
See how it scores against the Staff Engineer, Agentic AI posting at Clera — free, in seconds.
Don't guess if your resume is good enough.
See how it scores against the Staff Engineer, Agentic AI posting at Clera — free, in seconds.
About the Role
This senior technical leadership position is central to an enterprise AI platform for hardware engineers. You will lead the agent intelligence layer, transforming engineering intent into automated workflows across CAD, simulation, and PLM tools. Reporting to the CTO, you will guide a team and significantly impact the product's value to enterprise customers.
Responsibilities
- Own the core agent intelligence layer that executes multi-step workflows across complex desktop engineering software.
- Drive agent task success rate by defining evaluation frameworks, establishing baselines, and iterating systematically on completion metrics.
- Set and enforce per-task token budgets, tracking cost per completed workflow to ensure commercial viability.
- Design rigorous, reproducible evaluation infrastructure grounded in validated real user stories rather than synthetic tasks.
- Lead user story mapping and validation through direct interviews with engineers and close collaboration with domain experts.
- Translate every validated user story into a concrete test case, closing the loop between user research and agent benchmarking.
- Make foundational architecture decisions covering tool-calling strategies, state management, error recovery, model routing, and context management.
- Act as a player-coach: write production code, review architecture decisions, unblock teammates, and raise overall engineering standards.
- Collaborate cross-functionally with integrations, product, and customers during proofs-of-concept to align agent behavior with real-world usage.
Requirements
- 7+ years of software engineering experience, with at least 2 years building LLM-based agents that take real-world actions.
- Exceptional technical depth in agentic systems, including model selection, context and window management, retrieval, tool calling, and orchestration patterns.
- Demonstrated experience building evaluation and benchmarking frameworks that measure task completion, cost efficiency, and failure modes.
- Strong Python proficiency and hands-on familiarity with LLM tooling: function calling, tool APIs, observability and tracing, and evaluation frameworks.
- Proven track record shipping AI or LLM tooling on top of proprietary engineering data or desktop engineering software, such as agents or MCP servers over CAD, PLM, simulation, or similar systems. General-purpose chatbot or web-app RAG work alone is not sufficient.
- Experience setting technical direction and reviewing code for small engineering teams while continuing to write production code yourself.
- Experience with desktop automation or programmatic application control, such as COM or similar interfaces.
- Background in mechanical engineering, CAD/CAE, PLM, or an adjacent engineering-software domain.
- Familiarity with deploying agents on locked-down enterprise workstations and the associated security and operational constraints.
- Published work, public benchmarks, or open-source contributions in agentic AI are a strong plus.
Skills
- LLM-based agents
- Agentic systems
- Model selection
- Context and window management
- Retrieval
- Tool calling
- Orchestration patterns
- Evaluation frameworks
- Benchmarking
- Task completion measurement
- Cost efficiency measurement
- Failure mode analysis
- Python
- LLM tooling
- Function calling
- Tool APIs
- Observability
- Tracing
- Desktop automation
- Programmatic application control
- COM interfaces
Location
- San Francisco, California, United States
Work Type
- On-site
Experience Level
- Senior
- 7+ years of software engineering experience
- 2+ years building LLM-based agents
Salary/Compensations
- $160,000 to $250,000 USD annually, plus equity
Benefits
- Equity