Enterprise GenAI & Agentic AI Architect

Tata Consultancy Services; New York (NY); On-site; USD 150,000 - 170,000; Full time

Job summary

Tata Consultancy Services in New York is seeking a leader to architect and implement enterprise-scale AI, GenAI, and Agentic AI solutions across Banking, Wealth, Payments, and Risk. You will drive AI strategy, build scalable platforms, and ensure governance, security, and regulatory compliance.

The role demands hands-on expertise with GPT/GenAI, LangChain, Python, microservices, and cloud environments, guiding global teams and stakeholders toward production-ready AI capabilities.

Qualifications

• Hands-on experience with GenAI/AI platforms, enterprise-scale architectures, and governance.
• Strong Python development, API design, and microservices experience.
• Familiarity with cloud AI services and MLOps tooling.

Responsibilities

• Define enterprise AI/GenAI architecture, standards, and roadmaps.
• Design and deliver GenAI, RAG, multi-agent, and intelligent automation solutions.
• Architect AI platforms leveraging LLMs, vector databases, model orchestration, and reusable AI services.
• Lead AI use cases across banking domains such as KYC, AML, Fraud, Wealth, and Operations.
• Establish governance, model risk management, security guardrails, and observability frameworks.
• Partner with CTOs, Product Owners, Data Scientists, and Engineering teams to productionize AI solutions.
• Mentor architects and engineering teams on AI最佳实践.

Skills

GPT/GenAI expertise

Python

REST APIs

Kubernetes

Cloud platforms

Education

Bachelor's degree in Computer Science

Tools

LangChain

LangGraph

Docker

Terraform

Job description

Tata Consultancy Services in New York is seeking a leader to architect and implement enterprise-scale AI, GenAI, and Agentic AI solutions across Banking, Wealth, Payments, and Risk. You will drive AI strategy, build scalable platforms, and ensure governance, security, and regulatory compliance.

The role demands hands-on expertise with GPT/GenAI, LangChain, Python, microservices, and cloud environments, guiding global teams and stakeholders toward production-ready AI capabilities.