Senior Software Engineer – Applied AI Systems
About The Position
We’re looking for Senior Software Engineers to take full ownership of delivering working systems from prototypes and high-level specs — taking ideas from the research team, turning them into production-quality systems, and shipping them quickly. You’ll work closely with researchers, ML engineers, and leadership to turn ambitious ideas into real products. You'll be expected to move fast, handle ambiguity, and fill the critical execution gap between research and production. This role is perfect for someone who thrives on shipping — who sees incomplete specs as an opportunity, not a blocker — and who wants to build systems that work reliably, at scale, and in the real world. 📍 This is an onsite role based in our SF office (345 California St.)
Requirements
- 5+ years of hands-on software engineering experience
- Proven ability to execute on incomplete specs and drive projects to completion
- Strong experience writing production-quality code (Python/Go, knowledge of Rust is a plus but not mandatory)
- Comfortable building full-stack systems (APIs, data pipelines, microservices, internal tools)
- High standards for code quality, maintainability, and correctness
- Comfortable in fast-moving, ambiguous environments where priorities shift quickly
- Bias for ownership: you see what needs to get done and take responsibility for delivering
- Deep understanding of LLM architecture and inference-time optimization.
- Strong knowledge of the agentic ecosystem (frameworks, tools, MCP servers, MAS architectures).
- Track record of rapid prototyping in the LLM/agent space.
Nice To Haves
- Experience supporting ML research or building ML infrastructure is a plus
- Experience orchestrating and evaluating complex multi-agent systems.
Responsibilities
- Translate research prototypes and high-level concepts into production-quality software
- Own deliverables end-to-end: take specifications, clarify requirements, and execute to completion
- Build systems that are correct, reliable, maintainable, and performant
- Work closely with ML researchers and engineers to integrate research outputs into functional systems
- Own critical engineering tasks with high standards and attention to detail — data pipelines, API integrations, testing, error handling, system integration, and more
- Participate in code reviews, technical discussions, and architecture planning
- Contribute to improving processes for how we build, ship, and deliver features across teams
Benefits
- Competitive salary and early-stage equity package
- A high-trust, execution-first culture with minimal bureaucracy
- Direct ownership of meaningful projects with real business impact
- A rare opportunity to sit at the interface between deep research and real-world productization
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed
Number of Employees
1-10 employees
