Senior Python AI Solution Engineer

We are seeking a Senior Python AI Solution Engineer with strong software engineering fundamentals and hands-on experience building production AI and LLM applications. The ideal candidate combines deep expertise in Python, RAG, AI agents, APIs, cloud services, system integration, and production deployment with sharp analytical thinking and sound decision-making. You will act as a trusted technical partner to customer leadership, helping guide the direction of AI initiatives.

Design and build production-grade AI and LLM applications using Python Develop and maintain RAG pipelines and AI agent architectures Build and integrate APIs to support AI-driven solutions Deploy and manage AI systems across cloud environments Ensure secure and scalable system integration across platforms Collaborate with customer Technical Leadership to define project direction and architecture Apply analytical rigor to evaluate technical trade-offs and recommend solutions Prototype and validate AI concepts using appropriate frameworks and tools Support experimentation and model tracking throughout the development lifecycle Translate business requirements into robust technical implementations 3+ years of professional software engineering experience, with significant hands-on work in production AI and LLM applications Proficiency in Python 3.11/3.12+ as a primary development language Expertise in LLM application and agent frameworks such as LangChain, LlamaIndex, and PydanticAI Knowledge of Hugging Face Models/Datasets, sentence-transformers, and tokenizers Familiarity with Python project and dependency management tools such as uv, venv, and Poetry Skills in code quality tools including Ruff, Pytest, and Jupyter Background in machine learning libraries such as NumPy, pandas/Polars, and scikit-learn Understanding of deep learning frameworks such as PyTorch and TensorFlow/Keras Competency in vector search and RAG infrastructure such as FAISS, Qdrant, Chroma, Weaviate, Milvus, or pgvector with PostgreSQL Experience with AI API and deployment tools such as FastAPI, Pydantic, and Uvicorn Qualifications in containerization and orchestration tools such as Docker and Kubernetes Capability to work with data infrastructure technologies such as PostgreSQL, Redis, and Apache Kafka English proficiency at B2 level or higher Experience with TRL for LLM post-training Knowledge of DSPy for programmatic LLM pipelines Familiarity with LiteLLM for unified access to multiple LLM APIs Skills in experiment tracking tools such as MLflow and Weights & Biases Showcase of AI application UI development using Streamlit, Gradio, or FastAPI with React/Next.js/Angular 19+