Senior Software Engineer (Agents)

Location: San Francisco CA
Work Arrangement: On-site 5 days per week
Employment Type: Full-time
Experience: 310 years
Base Salary: $180000$330000
Equity: Competitive equity
Visa Sponsorship: Open to visa transfers and new sponsorships including OPT H-1B and TN

Were working with an early-stage AI company building intelligent software that automates complex engineering workflows. Its platform uses AI agents to operate professional engineering applications helping teams accelerate the design and development of complex physical products.

The company is developing a new category of agentic software for hardware and engineering teams bringing AI into workflows that have traditionally required extensive manual interaction with specialized desktop applications.

This is a small highly technical team where engineers have significant ownership over core product development. The company is based in San Francisco and works together in person five days a week.

• Build and own core components of an agentic system including tool calling state management context management error recovery and model routing.

• Design reliable systems that can execute complex multi-step workflows across desktop engineering applications.

• Optimize agent performance across latency reliability and cost including token efficiency and per-workflow budgets.

• Build production systems that interact with real desktop applications in secure and restricted enterprise environments.

• Own significant pieces of the agent infrastructure from design through implementation and production deployment.

• Help design and develop evaluation infrastructure to measure agent performance against real-world engineering workflows.

• Build reproducible and challenging benchmarks based on actual user requirements rather than purely synthetic tasks.

• Work with domain experts and user researchers to understand engineering workflows and translate them into measurable evaluation cases.

• Identify gaps in agent capabilities and systematically improve the percentage of workflows the system can complete end to end.

• Measure success through task completion rates workflow coverage reliability and token efficiency.

• Write high-quality maintainable production code and contribute to thoughtful architectural decisions.

• Participate in code reviews and help establish strong engineering standards across the team.

• Collaborate with AI engineers product integration teams researchers and domain experts.

• Work closely with customers during proof-of-concept engagements to understand real-world usage and improve agent behavior.

• Help shape the technical direction of the core agent platform.

• 310 years of professional software engineering experience building shipping and maintaining production systems.

• Strong computer science fundamentals and sound software engineering judgment.

• Experience building backend systems infrastructure distributed systems or complex software applications.

• Comfortable owning technical problems end to end from understanding requirements to implementation testing and production reliability.

• Interested in AI agents and the engineering challenges involved in making them reliable efficient and useful in real-world environments.

• Able to reason about multi-step workflows state management failure handling concurrency and system performance.

• Comfortable working in a fast-paced early-stage startup environment with significant individual ownership.

Important: Prior experience building LLM agents is not required. The team is open to strong software engineers who have the fundamentals and genuine interest in developing expertise in agentic systems.

Core requirements

• Strong software engineering and computer science fundamentals.

• Production experience with Python or another modern programming language.

• Experience designing and maintaining production systems.

• Strong understanding of backend systems APIs state management and system reliability.

• Ability to debug complex issues and reason through failure scenarios.

• Good engineering judgment and code quality.

Relevant areas of experience

• Agentic systems tool calling and orchestration.

• Distributed systems and workflow execution.

• Context management model routing and multi-step task execution.

• Evaluation frameworks testing infrastructure and benchmarking.

• Performance optimization latency reduction and cost efficiency.

• Desktop application automation or integrations with complex software.

• Experience working with LLMs AI agents or model-powered applications.

• Familiarity with agent observability and evaluation tools such as LangSmith or Logfire.

• Experience with CAD CAE PLM or other complex desktop engineering applications.

• Experience with COM or desktop application integrations.

• Exposure to enterprise environments locked-down workstations or on-premise deployments.

• Experience building reliable systems that operate across multiple tools and long-running workflows.

• Experience in an early-stage startup or a small high-ownership engineering team.

• Strong ownership mentality and ability to work independently.

• Curious about how complex systems work and motivated to solve difficult engineering problems.

• Comfortable working across technical and product boundaries.

• Practical and outcome-oriented with a focus on measurable product impact.

• Excited to work closely with a small team in a fast-paced in-person environment.

• Interested in the real-world application of AI rather than purely research-oriented work.

• Base Salary: $180000$330000.

• Equity: Competitive equity with a four-year vesting schedule.

• Work Arrangement: On-site five days per week in San Francisco.

• Visa: Open to transfers and new sponsorships including OPT H-1B and TN.

• Opportunity to work on a technically challenging product at the intersection of AI and engineering software.

• Significant ownership over core systems and product direction.

• Work on the core product: Own important parts of the agent system that directly determine the products capabilities and value.

• Solve real-world AI problems: Build agents that operate actual engineering software in real enterprise environments.

• High ownership: Work directly with senior technical leadership and take responsibility for meaningful parts of the platform.

• Help define a new category: Contribute to the development of reliable AI systems for complex engineering workflows.

• Small ambitious team: Join an in-person team where engineering decisions have a direct impact on the product.