Lead Python AI Solution Engineer

We are looking for aLead 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+