We are looking for a professional with solid experience in Python to work with Artificial Intelligence, especially LLMs and agents, on innovative projects.
Hands-on work with RAG, prompt engineering, development of agent flows and integrations in Python/TypeScript, including use of AWS.
Mastery of software engineering best practices, testing, observability, and memory/state management in AI applications is essential.

Hands-on development with LLMs: building features using LLMs, understanding model behavior, limitations, and fundamentals of tuning.
Implementation of RAG (Retrieval-Augmented Generation): document ingestion, chunking, embedding generation, vector search, and relevance tuning.
Experience with agent frameworks: developing single-agent flows and simple multi-agent flows using agentic frameworks.
Prompt engineering (practical): writing reliable prompts, handling edge cases, and mitigating hallucinations.
Proficiency in Python and TypeScript: production-level coding, asynchronous flows, and API integrations.
AWS fundamentals for AI workloads: deploying AI services, using managed cloud services, and basic cost awareness.
Memory and state management: conversational state control, session memory, and basic long-term storage patterns.
Testing and evaluation fundamentals: prompt testing, functional tests for AI flows, and simple evaluation metrics.
Observability: logging prompts and responses, failure tracing, and basic cost and latency monitoring.
Strong software engineering discipline: clean code, version control, code reviews, and sustainable, maintainable architecture.

Data Scientist / Data Analyst, AI & LLMs

Key skills