Company
Engineering
StaffEngineer—AgenticAI
Neural analysis suggests this role is
optimal for Senior candidates.
“Staff Engineer — Agentic AI. Skills: Agentic AI, LLM application architectures, Evaluation frameworks. Lead development of core agent intelligence. Execute multi-step workflows”
What You'll Achieve.
Ensure commercial viability; Improve completion metrics
Industry & Context.
Error recovery
What They're Looking For.
Must Have
7+ years in software engineering, 2 years building agentic LLM-based agents, Python skills, Experience with desktop automation
Nice to Have
Domain experience in mechanical engineering, Experience in CAD/CAE, Experience in PLM, Experience in adjacent industries, Understanding of enterprise deployment constraints, Track record contributing to public benchmarks, Track record contributing to publications, Track record contributing to open-source agentic AI projects
What You'll Do.
Lead development of core agent intelligence
Execute multi-step workflows
Own full product loop
Define agent capabilities
Build agent implementations
Benchmark agent implementations
Drive agent task success rate
Define evaluation frameworks
Iterate to improve metrics
Set per-task token budgets
Track cost per workflow
Build reproducible evaluation infrastructure
Lead user story mapping
Validate user stories
Collaborate with domain experts
Translate user stories
Create testable evals
Close loop between research and benchmarking
Own agent architecture decisions
Write production code
Raise engineering standards
Collaborate cross-functionally
How You'll Work.
Team & Collaboration
Cross-functionally with integrations; Cross-functionally with product; Cross-functionally with customers
Full Job Description
ABOUT THE ROLE We're hiring a senior technical leader to own the core agent intelligence that turns 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. You'll report to the CTO and serve as technical lead for a small team of AI engineers, a user researcher, and domain expert contractors in an early-stage, high-impact environment (Series A, Fortune 100 customers, direct line to leadership). WHAT YOU'LL DO - Lead development of the core agent intelligence layer that executes multi-step workflows across complex desktop engineering software. - 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, and raise engineering standards. - Collaborate cross-functionally with integrations, product, and customers during POCs to align agent behavior with real-world usage. WHAT WE'RE LOOKING FOR - 7+ years in software engineering, including at least 2 years building agentic LLM-based agents that act in the real world. - Deep experience
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