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.

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 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 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

📌 AI Engineer (Argentina)
🏢 EPAM Systems
📍 Argentina