Senior AI Engineer: Generative + Agentic ML Architect

Tata Consultancy Services; Town of Florida (NY); On-site; USD 100,000 - 130,000; Full time

Benefits offered by this job

Discretionary Bonus

Medical Coverage

Parental Leave

401K Plan

Training Reimbursement

Vacation & Holidays

Job summary

Tata Consultancy Services is seeking an AI Engineer in the United States to design, build, and deploy scalable AI/ML solutions. You will develop multimodal applications, implement agentic AI frameworks, and optimize end-to-end ML pipelines for business impact.

The role requires deep hands-on experience with ML frameworks, LangChain/ LangGraph, and modern AI tooling, along with collaboration across Product, Data, and Architecture teams. Strong production experience is essential.

Qualifications

• Design, build, and optimize machine learning pipelines.
• Strong fundamentals in Python and software design patterns.
• Experience with ML tools and frameworks (PyTorch, TensorFlow) in production.
• Experience with Generative AI, LangChain/LangGraph, and AI agents.

Responsibilities

• Design, develop, and deploy scalable AI and ML solutions to solve business problems.
• Build end-to-end ML pipelines from data ingestion to deployment and monitoring.
• Develop Generative AI applications using LLMs, RAG, and AI agents.
• Implement Agentic AI frameworks with LangGraph and LangChain.
• Create multimodal AI solutions integrating text, image, audio, and video.
• Collaborate with cross-functional teams to define AI strategy and roadmaps.

Tools

Python

NumPy

Pandas

Scikit-learn

XGBoost

LightGBM

PyTorch

TensorFlow

MLflow

Matplotlib

LangChain

LangGraph

LlamaIndex

FAISS

Pinecone

OpenAI API

Anthropic API

Gemini API

Job description

Tata Consultancy Services is seeking an AI Engineer in the United States to design, build, and deploy scalable AI/ML solutions. You will develop multimodal applications, implement agentic AI frameworks, and optimize end-to-end ML pipelines for business impact.

The role requires deep hands-on experience with ML frameworks, LangChain/ LangGraph, and modern AI tooling, along with collaboration across Product, Data, and Architecture teams. Strong production experience is essential.