Develop and optimize applications based on Large Language Models (LLMs), ensuring response quality and prompt efficiency;
Agent Orchestration: Design and implement complex flows and multi-agent systems using LangChain and LangGraph for reasoning automation;
Data Architecture for AI: Implement RAG (Retrieval-Augmented Generation) strategies, including vector databases and indexing techniques for semantic search;
Backend Development: Build robust, high-performance APIs in Python (FastAPI/Django) to serve AI models at scale;
Cloud Scalability: Develop and deploy solutions using the AWS ecosystem, focusing on AI services, serverless computing, and containers;
Quality and Monitoring: Establish model testing standards (evaluation of hallucinations, latency, and cost) and ensure the development lifecycle (LLMOps).

Advanced Python: Deep mastery of the language, including concurrency, static typing, and software engineering best practices (SOLID, Clean Code);
AI Frameworks: Strong experience building chains with LangChain and cyclical/graph workflows with LangGraph;
LLM Providers: Experience integrating models via APIs (OpenAI, Anthropic) and via AWS Bedrock;
Cloud Computing (AWS): Hands-on knowledge of Lambda, ECS/EKS, S3, and databases (RDS/DynamoDB);
Software Engineering: Proficiency with Git, Docker, and CI/CD pipelines applied to backend projects.

Back-End Developer III

Key skills