Back to SearchLead Python AI Solution Engineer
Remote in Argentina, & 4 others
AI Solution Engineering& 4 others
Looking for something else?
Find a vacancy that works for you. Send us your CV to receive a personalized offer.
Find me a job
Choose an option
We are looking for a Lead Python AI Solution Engineer to build production AI and LLM solutions, shape architecture and deliver reliable, scalable systems. You will lead Python-based RAG and agent work, integrate APIs, and partner with client technical leadership to steer decisions and delivery.
Responsibilities
- Design and deliver production-ready AI and LLM applications in Python
- Develop and sustain RAG pipelines along with AI agent architectures
- Implement and connect APIs that enable AI-driven capabilities
- Deploy and operate AI systems across cloud environments
- Ensure secure, scalable integration across platforms and services
- Collaborate with client Technical Leadership to set project direction and architecture
- Evaluate technical trade-offs with strong analytical judgment and recommend solutions
- Prototype and prove AI concepts using the right frameworks and tools
- Support experimentation and model tracking throughout the development lifecycle
- Translate business requirements into dependable technical implementations
Requirements
- 5+ years of professional software engineering experience, including substantial hands-on delivery of production AI and LLM applications
- High proficiency with Python 3.11/3.12+ as your primary programming language
- Deep experience with LLM application and agent frameworks such as LangChain, LlamaIndex, and PydanticAI
- Working knowledge of Hugging Face Models/Datasets, sentence-transformers, and tokenizers
- Hands-on familiarity with Python project and dependency tooling such as uv, venv, and Poetry
- Solid command of code quality and development tools including Ruff, Pytest, and Jupyter
- Strong background with machine learning libraries such as NumPy, pandas/Polars, and scikit-learn
- Practical understanding of deep learning frameworks such as PyTorch and TensorFlow/Keras
- Proven track record implementing vector search and RAG infrastructure such as FAISS, Qdrant, Chroma, Weaviate, Milvus, or pgvector with PostgreSQL
- Hands-on experience building AI APIs and deployment components with FastAPI, Pydantic, and Uvicorn
- Demonstrated skills in containerization and orchestration using Docker and Kubernetes
- Experience working with data infrastructure technologies such as PostgreSQL, Redis, and Apache Kafka
- English proficiency at B2 level (Upper-Intermediate) or higher
Nice to have
- Experience applying TRL for LLM post-training
- Knowledge of DSPy for building programmatic LLM pipelines
- Familiarity with LiteLLM to unify access to multiple LLM APIs
- Experience with experiment tracking tools such as MLflow and Weights & Biases
- Portfolio of AI application UI work using Streamlit, Gradio, or FastAPI with React/Next.js/Angular 19+