Lead AI/ML Engineer
Posted
Summary
Lead AI/ML engineer at Staples in Chennai who architects agentic AI and Model Context Protocol (MCP) solutions, builds full-stack AI apps (React, Node.js, TypeScript), and integrates LLMs (Claude/GPT) with RAG, prompt engineering, and MLOps tooling like PyTorch, Kubernetes, Vertex AI, and Azure ML.
- Design and architect AI-powered solutions using Model Context Protocol (MCP) and agentic AI frameworks. Define AI integration patterns aligned with Staples technical strategy and business objectives.
- Architect agentic AI systems that can autonomously reason, plan, and execute complex workflows. Implement multi-step reasoning, function calling, and tool orchestration for intelligent automation.
- Master Model Context Protocol (MCP) implementation to enable seamless integration between AI models and various data sources, APIs, and enterprise systems. Design MCP servers and clients for optimal performance.
- Develop full-stack AI applications using React, Next.js, Node.js, and TypeScript that leverage advanced AI capabilities. Build responsive interfaces that interact with AI backends and agentic systems.
- Evaluate, experiment with, and integrate cutting-edge LLMs and AI frameworks such as Claude and GPT models. Stay current with rapid advancements in AI and provide recommendations on adoption.
- Implement prompt engineering best practices, fine-tuning strategies, and retrieval-augmented generation (RAG) systems. Design AI solutions that balance accuracy, cost, latency, and user experience.
- Lead governance and security initiatives for AI systems, including bias mitigation, explainability, compliance, and responsible AI practices. Establish frameworks for monitoring AI model behavior.
- Mentor engineering teams on AI integration, agentic patterns, and MCP architecture. Drive knowledge sharing through documentation, workshops, and collaboration to accelerate AI adoption.
Requirements
Primary skills:
Agentic AI ,Python, PyTorch, TensorFlow, Scikit-learn, Hugging Face, LangChain, LLMs, RAG, Prompt Engineering, Feature Engineering, Model Training & Fine-tuning, MLflow, Kubeflow, Docker, Kubernetes, Vertex AI, Azure ML, SQL, Spark, Vector Databases, AI System Architecture, MCP, REST APIs, CI/CD for ML, Model, Semantic Search, Couch DB
Good to have skills:
FAISS, Pinecone, Weaviate, Solace, Airflow, dbt, Snowflake, BigQuery, Databricks, FastAPI, Flask, Pandas, NumPy, GAN, VAE, Diffusion Models, Embeddings, Feature Stores, Data Drift Detection, Multi-agent Systems, Responsible AI, Bias Auditing
Skills
- Agentic AI
- AI
- Ai Enablement
- Airflow
- API
- Automation
- Azure
- BigQuery
- CI/CD
- Databricks
- dbt
- Docker
- Embeddings
- FAISS
- FastAPI
- Feature Engineering
- Fine Tuning
- Flask
- Hugging Face
- Kubeflow
- Kubernetes
- LangChain
- LLM
- Machine Learning
- MCP
- MLflow
- Next.js
- Node.js
- NumPy
- pandas
- Pinecone
- Prompt Engineering
- Python
- PyTorch
- RAG
- React
- REST
- scikit-learn
- Semantic Search
- Snowflake
- Spark
- SQL
- TensorFlow
- TypeScript
- Vector Databases
- Vertex AI
- Weaviate