AI/ML Architect - Python/LLM

Description :

Job Description :

Key Responsibilities :

- Define and govern end-to-end AI/ML and GenAI architectures aligned with business and enterprise standards.

- Evaluate, select, and standardize AI/ML tools, frameworks, and platforms across the organization.

- Drive AI/ML and GenAI POCs from ideation to production deployment.

- Design scalable solutions for LLMs, RAG-based systems, and agentic / multi-agent architectures.

- Establish and lead the AI Center of Excellence (COE), including reference architectures, accelerators, and best practices.

- Provide technical leadership, architecture reviews, and solution governance.

- Lead training programs, hands-on workshops, and knowledge-sharing sessions for AI/ML teams and stakeholders.

- Mentor and coach engineers on AI engineering, MLOps, deployment, and architectural best practices.

- Collaborate with business, product, and engineering teams to translate business problems into AI-driven solutions.

- Ensure solutions adhere to security, scalability, performance, and Responsible AI standards.

Skills Required :

- Hands-on experience with multiple LLMs (OpenAI / Azure OpenAI, Gemini, Claude, LLaMA, Mistral).

- Expertise in RAG architectures, embeddings, and vector databases (FAISS, Pinecone, Weaviate, Chroma, Milvus).

- Experience with agentic and multi-agent systems, including MCP / A2A concepts.

- Proficiency in modern GenAI frameworks (LangChain, LangGraph, LlamaIndex, CrewAI, AutoGen, Google ADK).

- Strong programming experience in Python; API development using FastAPI and Flask.

- Experience with ML frameworks (PyTorch, TensorFlow, Scikit-learn).

- Hands-on experience with cloud AI platforms (Azure, AWS, GCP).

- Expertise in deployment, CI/CD, containerization, and MLOps using Docker, Kubernetes, MLflow, Azure ML, SageMaker, or Vertex AI.

- Proven experience leading AI teams and COE initiatives.

- Strong capability in training, mentoring, and upskilling technical teams.

- Ability to define and enforce AI governance, risk, compliance, and Responsible AI practices.

- Excellent stakeholder management, communication, and strategic thinking skills.