Senior AI Engineer

Every AI agent's investigation is only as good as the LLM system underneath it. Get the retrieval, context, and prompting wrong, and the agent looks smart in a demo but falls apart on a real customer's data. As a Senior AI Engineer, you'll build the LLM-powered systems behind our security agents: retrieval workflows, context management, agent prompts, and structured output pipelines. This role is distinct from traditional ML engineering. Instead of training models from scratch, you'll compose, optimize, and scale AI systems that solve complex enterprise problems, working closely with product, platform, and backend teams to get them into production.

- Architect and build LLM-powered systems, including retrieval workflows, context management, agent prompts, and structured output pipelines.

- Orchestrate AI workflows using LangChain, LlamaIndex, or similar frameworks, and integrate them with product APIs and backend services.

- Own prompt engineering and iteration, refining prompts, templates, and context strategies to meet product quality and reliability goals.

- Track real-world evaluation metrics such as usefulness, factual correctness, latency, and user experience impact, not just classic accuracy.

- Work closely with product, platform, and backend teams to ensure integrations land cleanly.

- Build reliable, scalable deployments that hold up on performance, cost efficiency, and observability in production.

- 6+ years of software engineering experience, including at least 1 year building AI in production.

- BS in Computer Science or a related field.

- Shipped LLM applications in production, not just prototypes, using large models in ways that meaningfully mattered to the product.

- Strong coding skills in Python (or equivalent), with experience in API design, backend integration, database systems, and cloud deployment.

- Hands-on experience with RAG, vector databases (Pinecone, Weaviate), and workflow frameworks like LangChain or Dust.