We are seeking a Senior AI Engineer to design and productionize GenAI and agentic solutions that orchestrate models, tools, and enterprise data to solve complex, multi-step workflows. You will build reliable RAG, evaluation, and observability capabilities and deliver robust Python services. Responsibilities Design and productionize GenAI and agentic systems that orchestrate models, tools, enterprise data, state and memory, and human input Develop agent orchestration patterns for planning, routing, tool calling, structured outputs, workflow graphs, handoffs, retries, and recovery Build reusable agent tools, APIs, and connectors with clear schemas, authentication, permissions, sandboxing, and least-privilege access Build and optimize RAG and enterprise search using embeddings, vector databases, hybrid retrieval, metadata filtering, reranking, grounding, and citations Create evaluation and test frameworks that measure task completion, groundedness, retrieval quality, tool-use accuracy, robustness, and end-to-end outcomes Implement observability for prompts, traces, retrieval, model behavior, token usage, cost, latency, failures, and user feedback to drive improvements Develop production-grade Python and FastAPI services with automated testing, CI/CD, load testing, caching, fallbacks, and performance optimization Apply Responsible AI and security practices including guardrails, content filtering, privacy controls, authorization, auditability, and escalation paths Collaborate with product, engineering, and domain partners to translate needs into measurable workflows, prototype quickly, and scale successful solutions Requirements 3+ years experience delivering production-ready AI or GenAI solutions Senior-level ownership skills to lead technical decisions for agentic workflows Strong project execution skills to take prototypes to reliable production releases Advanced Python skills for production software engineering and data handling FastAPI development skills including async APIs, testing, and service design Agent orchestration skills with tool/function calling, structured outputs, state and memory, retries, and human-in-the-loop controls RAG engineering skills using embeddings, vector databases, hybrid retrieval, reranking, grounding, and citations Evaluation framework skills for LLM and agentic quality, safety, and regression testing Observability skills for prompts, traces, tool calls, retrieval, cost, latency, and failures Responsible AI and security skills including guardrails, prompt-injection defenses, and privacy controls Upper-Intermediate English skills (B2, Upper-Intermediate) Nice to have Amazon Web Services skills including cloud-native deployment patterns Data governance skills for enterprise content and access controls Gen AI assisted development skills to accelerate delivery and maintain quality Machine learning engineering skills for model evaluation and system integration Responsible AI skills for safety, compliance, and risk management
