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We are seeking an AI Engineer to design and deliver production-grade GenAI and agentic solutions that connect models, tools, and enterprise data to complete complex workflows. You will build reliable orchestration, RAG search capabilities, and evaluation/observability to improve quality and safety.
Responsibilities
- Design and productionize GenAI and agentic systems that orchestrate models, tools, data, state, and human input across multi-step workflows
- Develop agent orchestration patterns including planning, routing, structured outputs, workflow graphs, retries, error recovery, and human-in-the-loop controls
- Build RAG and enterprise search solutions using embeddings, vector databases, hybrid retrieval, metadata filtering, query transformation, reranking, grounding, and citations
- Create evaluation and test frameworks that measure task completion, groundedness, retrieval quality, tool-use accuracy, safety, robustness, and regression
- Implement observability for prompts, traces, retrieval, tool calls, token usage, cost, latency, failures, and user feedback to drive continuous improvement
- Develop production-grade Python and FastAPI services with automated tests, CI/CD, caching, fallbacks, and performance and cost optimization
- Apply Responsible AI and security practices including guardrails, content filtering, privacy controls, least-privilege access, auditability, and escalation paths
- Build reusable tools, APIs, and connectors with clear schemas, permissions, authentication, sandboxing, and least-privilege access
- Collaborate with product, engineering, and domain experts to define measurable outcomes, prototype solutions, and scale successful capabilities
Requirements
- 2+ years of experience delivering production-ready AI or GenAI solutions
- Hands-on agentic application experience with tool/function calling, routing, and structured outputs
- Solid leadership skills to collaborate with cross-functional partners and align on measurable outcomes
- Workflow delivery experience translating business needs into agentic workflows from prototype to scale
- Strong Python skills for production services, asynchronous workflows, and data handling
- API engineering skills with FastAPI, automated testing, and CI/CD practices
- Strong RAG and vector database skills including embeddings, hybrid retrieval, reranking, and citations
- Security and Responsible AI skills including guardrails, privacy controls, and prompt-injection defenses
- Strong problem-solving skills for reliability, error recovery, and performance optimization
- Upper-Intermediate English (B2) proficiency
Nice to have
- Amazon Web Services (AWS) experience with managed GenAI platforms such as Bedrock
- Data governance knowledge for permissions, auditability, and enterprise controls
- Gen AI assisted development practices for accelerating delivery with quality safeguards
- Machine learning engineering experience for model evaluation and deployment readiness
- Responsible AI experience with safety testing and governance processes