AI Agent Developer

Role Overview You'll design agent systems that can reason over structured and unstructured business context, call tools safely, recover from failure, and generate outputs that are trustworthy in enterprise settings. This is not prompt-only work. You'll be working across orchestration, evaluation, retrieval, tool contracts, state, and product behavior to create agents that are useful in production, not just impressive in demos. Apply context Share one agent workflow you built that had to handle uncertainty, tool failure, or low-quality source data. What You'll Own Design agent workflows spanning tool use, retrieval, memory, and handoffs. Build evaluation harnesses for reliability, safety, and business correctness. Work with product engineers to embed agents into production interfaces. Improve latency, cost efficiency, and failure recovery under real user traffic. What We're Looking For Experience building LLM or agent products beyond prototypes. Strong TypeScript or Python skills. Practical understanding of retrieval, tool calling, and prompt/system design. Ability to debug complex behavior across distributed systems and model layers. BSc in Computer Science, Software Engineering, AI, or equivalent applied experience.