The company is hiring a Senior Fullstack AI Engineer to design, build and ship production-grade retrieval-augmented generation (RAG) and agentic systems on Azure AI Foundry for our AI products.
You will own the end-to-end lifecycle of LLM features: ingestion and chunking pipelines, vector and hybrid search, prompt and agent orchestration, evaluation, and deployment on Azure. You will work closely with product, domain experts and client engineering teams, and set technical direction for less experienced engineers.
Key responsibilities:
● Design and build RAG pipelines end to end: document ingestion, parsing (PDF, scanned documents, structured and semi-structured data), chunking strategies, embeddings, hybrid (vector + keyword) search and reranking.
● Build and operate on Azure AI Foundry: model deployments (Azure OpenAI and open weight models), prompt flows, Agent Service, Azure AI Search, evaluations and content safety.
● Implement agentic workflows (tool calling, multi-step planning, function orchestration) with frameworks such as Semantic Kernel, LangGraph or Autogen.




● Own evaluation: build offline and online eval harnesses (groundedness, relevance, faithfulness, latency, cost), golden datasets and regression gates in CI.
● Take systems to production: latency and cost optimization, caching, observability (Azure Monitor, tracing), rate limiting, failover across model deployments.
● Handle sensitive data correctly: PII redaction, compliance-aligned controls, Azure private networking, managed identity, Key Vault, RBAC.
● Partner with product managers and domain experts to turn ambiguous requirements into shippable features.
● Mentor engineers, review designs and code, and set standards for prompt engineering, evaluation and LLMOps across teams.
● Contribute to client-facing technical discussions, architecture reviews and estimates.
● Build the full feature surface, not just the model layer: backend APIs, data persistence, and the front-end chat, copilot or workflow

📌 RAG / Azure AI Foundry (Buenos Aires)
🏢 Conexionhr
📍 Buenos Aires