Senior AI Python Technical Lead

Job description

Senior AI & Python Technical Lead We are looking for an experienced Senior AI & Python Technical Lead to lead the design, architecture, and delivery of enterprise-scale AI, Generative AI, and cloud-native solutions. This role requires a strong technical leader with team management experience, capable of driving solution architecture, mentoring engineers, stakeholder engagement, technical governance, and end-to-end delivery of production-grade AI platforms. Your Role Lead and mentor AI Engineers, Python Developers, ML Engineers, Data Engineers, MLOps Engineers, Cloud Engineers, and Solution Architects. Own technical architecture, technology strategy, engineering standards, and solution delivery. Drive AI innovation, PoCs, reusable frameworks, enterprise AI adoption, and platform modernization. Engage with business stakeholders and lead cross-functional teams to deliver scalable, secure, and high-performing AI solutions. Establish engineering best practices across AI, software engineering, DevOps, cloud, and MLOps. Who You Are: Bachelor’s or Master’s degree in computer science, Artificial Intelligence, Machine Learning, Data Science, Software Engineering or a related discipline. At least 10 years of hands-on experience in Python software engineering and enterprise application development. At least 5 years of experience designing, developing and deploying production-grade AI/ML and Generative AI solutions. At least 3 years of experience architecting Retrieval-Augmented Generation (RAG), Agentic AI and enterprise AI platforms. Proven experience leading technical teams as a Technical Lead, AI Engineering Manager, Principal Engineer or Solution Architect. Experience delivering enterprise AI platforms on AWS or other major cloud providers. Strong experience in stakeholder management, engineering governance, solution architecture and large-scale Agile delivery. Technical Skills Programming & Backend Python, SQL, NoSQL FastAPI, Flask, Django REST APIs, GraphQL, Microservices, Distributed Systems AI / Machine Learning PyTorch, TensorFlow, Scikit-learn Hugging Face Transformers LangChain, LlamaIndex, DSPy Generative AI LLMs, RAG, GraphRAG AI Agents, Multi-Agent Systems Prompt Engineering, Context Engineering Embeddings, Semantic Search, Hybrid Search Agent Frameworks LangGraph CrewAI Microsoft AutoGen LangChain Agents Vector Databases Pinecone, Qdrant, Weaviate ChromaDB, Milvus, FAISS LLMOps & Evaluation LangSmith, Ragas, DeepEval OpenAI Evals, MLflow Model Monitoring, Prompt Lifecycle Management, AI Observability AI Security & Governance NeMo Guardrails, Llama Guard, Amazon Bedrock Guardrails Prompt Injection Protection, PII Protection, Responsible AI, AI Governance Cloud & AI Platforms AWS Bedrock, SageMaker ECS, EKS, Lambda, API Gateway EC2, S3, DynamoDB, OpenSearch EventBridge, Step Functions, CloudWatch, IAM DevOps & MLOps Docker, Kubernetes Terraform, Jenkins GitHub Actions, ArgoCD CI/CD, GitOps, Model Deployment, Infrastructure as Code