Enterprise AI Architect - GenAI, LLMs & MLOps

Tata Consultancy Services; Atlanta (GA); On-site; USD 100,000 - 150,000; Full time

Benefits offered by this job

Discretionary incentive

Comprehensive medical coverage

Parental leave benefits

401K plan and retirement support

Job summary

Tata Consultancy Services seeks an experienced AI Architect to define end-to-end architectures for Generative AI, Agentic AI, ML and intelligent automation within the airline domain.

You will translate business priorities into scalable AI capabilities, establish standards for model integration, and design reusable AI services spanning digital channels, operations, and enterprise functions. This role requires collaboration with business and technology teams.

Qualifications

• Define end-to-end architecture for Generative AI, Agentic AI, ML and automation solutions.
• Translate airline priorities into scalable AI capabilities, reference architectures and roadmaps.
• Design reusable AI services across digital channels, airline ops, IT ops, customer service, engineering.

Responsibilities

• Establish architecture standards for model integration, orchestration, data access, APIs, security and deployment.
• Review solution designs and ensure alignment with enterprise standards and target architecture.
• Architect enterprise-grade LLM solutions using RAG, knowledge grounding, tool integration and multi-agent orchestration.
• Define patterns for agent planning, reasoning, memory, function calling, outputs and secure tool access.
• Collaborate with business teams to identify AI opportunities and design customer-centric AI capabilities.

Skills

AI Architecture

LLM Orchestration

MLOps

Cloud Native

Tools

LangChain

LangGraph

Semantic Kernel

CrewAI

Job description

Tata Consultancy Services seeks an experienced AI Architect to define end-to-end architectures for Generative AI, Agentic AI, ML and intelligent automation within the airline domain.

You will translate business priorities into scalable AI capabilities, establish standards for model integration, and design reusable AI services spanning digital channels, operations, and enterprise functions. This role requires collaboration with business and technology teams.