A high-growth AI-native startup is hiring an AI Engineer in San Francisco to design, build and ship LLM-powered product features and agentic workflows into production.
This is a build role focused on the applied AI stack: prompts, retrieval, tools, agents, evals and the glue that connects them to a real product. You'll work close to product and real users, not inside a research lab.
Role: AI Engineer
Salary: $300,000 - $400,000 plus equity
Location: San Francisco, 5 days per week in office
What you'll be doing:
- Design and ship production LLM features and agents using Python and TypeScript
- Build the applied AI toolkit end to end: tool and function calling, RAG, vector search, structured output, prompt management, context handling
- Work directly with foundation model APIs (Anthropic, OpenAI, Google) and open-source models where it makes sense
- Build evaluation pipelines (Braintrust, LangSmith or custom) so quality is measurable rather than anecdotal
- Integrate agents into existing product surfaces built in React and Next.js
- Own cost, latency and reliability of the AI layer as first-class concerns
- Use AI tooling (Claude, Cursor and similar) across your workflow to compress the build cycle
What you'll need:
- Strong Python and TypeScript, with real production experience shipping LLM-powered features
- Practical grasp of the applied AI stack: function calling, RAG, vector databases, structured output, prompt engineering, context management
- Comfort with at least one agent framework or SDK, with a view on why the abstractions exist
- Experience building evals and guardrails for LLM output
- Solid API, integration and backend engineering fundamentals
- Fluent in modern AI engineering tools and able to use them to raise output
- Happy working 5 days a week in-person with a small, high-intensity team
Nice to have:
- Prior work on agentic systems in production (not just prototypes)
- Experience with multimodal models (vision, audio, video)
- Exposure to fine-tuning or post-training of foundation models
This role would suit an AI engineer who wants to ship real LLM product into users' hands, not write another whitepaper.
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AI Engineer
Digital Waffle
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