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Project BriefWe're building AI-powered products, primarily leveraging off-the-shelf LLM APIs, while also partnering with our Applied Science teams to integrate custom models when needed.
You'll own end-to-end development of AI features — from prototyping to production — focused on reliability, accuracy, and scalable delivery.Project BriefWe're building AI-powered products, primarily leveraging off-the-shelf LLM APIs, while also partnering with our Applied Science teams to integrate custom models when needed.
You'll own end-to-end development of AI features — from prototyping to production — focused on reliability, accuracy, and scalable delivery.Must-HavesStrong Python engineering skills and experience delivering production systemsHands-on experience building with LLM APIs (OpenAI, Anthropic, etc.) and deploying AI features end-to-endExperience with LangChain / LangGraph — including Prompt Engineering, Token Management, and Agent creation with tool-based workflowsExperience building agentic workflows (tool use, routing, memory, safety/guardrails), ideally with MCPSolid understanding of RAG concepts — retrieval, chunking, embeddings, re-ranking, and evaluationPractical AWS experience, especially AWS Lambda and serverless architecture patternsBackend engineering experience: RESTful API design, webhook integration, JWT, pytest,



and observability tools like SentryExperience doing Git repository analysis — understanding large codebases, debugging, refactors, and code healthComfortable working in fast-moving product environments with high ownershipNice to HaveNextJS and TypeScript for frontend components and integrationAWS CDK for infrastructure-as-code and deploymentBroader AWS services knowledge: S3, CloudWatch, IAM, API GatewayExperience with NoSQL databasesExperience integrating or serving custom models (inference, model endpoints, monitoring)Familiarity with evaluation frameworks (offline tests, human feedback loops, regression suites)Strong software engineering fundamentals: testing, CI/CD, observability, performanceWhat You Will DoPlan and develop applications that include custom AI components — orchestration, evaluation, tooling, and integrationsBuild intelligent agents using LLMs and the MCP framework to enable context-aware automation and decision-makingAutomate internal workflows and operational processes using Python and AWS LambdaDevelop and improve RAG-based chatbots to increase response accuracy, grounding, and consistencyCollaborate with Applied Science teams to productionize custom models and connect them with product systemsDesign and maintain multi-agent AI pipelines, including fallback and graceful degradation strategies for reliabilityWhy You'll Want This Role

Postúlate en Kit Empleo: kitempleo.com.ar/empleo/moqes

📌 Remote Ai/Llm Engineer - Build Production Ai Pipelines (Godoy Cruz)
🏢 OneSeven Tech (OST)
📍 Godoy Cruz