Mid/Senior professional working with Python, AWS, and AI.
Enjoy working in a team and be collaborative in your responsibilities;
Be willing to challenge yourself and go beyond, embracing new growth opportunities;
Turn ideas into creative solutions and pursue quality in all your work;
Have strong problem-solving skills;
Be able and comfortable working independently and managing your own time;
Be interested in tackling challenging and innovative technological situations.

High-performance applications using Python and frameworks such as LangChain, LangGraph, Flask, Django, FastAPI, pytest, and asyncio.
Familiarity with development design patterns, for example: Creational (Factory Method, Abstract Factory, Builder);
Structural (Adapter, Bridge, Composite);
Behavioral (Chain of Responsibility, Command, Interpreter);
Knowledge of AWS and/or Azure tools and services.
Development best practices using SOLID principles.
Experience with containers: Docker, EKS, ECS, and AKS;
Experience with databases: NoSQL and relational; knowledge of DynamoDB and RDS is desirable.
Experience in CI/CD: GitHub Actions, GitLab, CodePipeline, CodeBuild, and other CI/CD tools.
Experience in the banking ecosystem: processes, services, etc.
Experience with observability.
Familiarity with tools such as Datadog and CloudWatch.
Analytical skills (troubleshooting).
Knowledge of language models (LLMs) such as GPT, Claude, Gemini, LLaMA.
Experience with LLM solutions: OpenAI, Azure OpenAI, or AWS Bedrock.
Use of frameworks such as LangChain, LangGraph, and Semantic Kernel.
Understanding of GenAI agent concepts: RAG (Retrieval-Augmented Generation), tool-based agents, embeddings, and vector stores (Weaviate, AI Search).
Building agents, copilots, and autonomous workflows with LLMs.
Understanding of traditional ML concepts: regression, classification, and testing.

Python Development, AWS, AI – Mid/Senior

Key skills