GCP, Vertex AI, Gemini APIs,Python

Tata Consultancy Services; India; On-site; INR 4,000,000 - 7,000,000; Full time

Job summary

Tata Consultancy Services seeks a senior Enterprise AI Architect to lead solution architecture for cloud-driven AI initiatives. You will collaborate with customers and stakeholders to translate business challenges into scalable AI solutions using Gemini, Vertex AI, and Google Cloud services.

You will design advanced AI systems, guide PoCs, and mentor engineering teams, delivering production-grade AI applications and governance models across enterprise deployments.

Qualifications

• 10+ years of software engineering with system design expertise.
• Hands-on experience in Python, APIs, microservices, and cloud-native apps.
• Extensive GCP, Vertex AI, Gemini APIs and AI/ML platform experience.
• Experience delivering enterprise AI solutions with LLMs, RAG, multi-agent AI.
• Proven ability to lead customer-facing solution architecture and executive engagements.
• Experience building AI accelerators, PoCs, and production-grade AI apps.
• Strong cloud architecture, Kubernetes, DevOps, CI/CD, and platform engineering.
• Deep data engineering know-how: vector DBs and knowledge retrieval.

Responsibilities

• Lead the solution architecture and tech strategy for enterprise AI and cloud transformation.
• Engage customers and stakeholders to translate business challenges into scalable AI solutions.
• Design and oversee AI-powered apps leveraging Gemini, Vertex AI, and Google Cloud services.
• Build complex AI architectures with RAG, Agentic AI, multimodal AI, and integrations.
• Lead discovery sessions, PoCs, and customer demonstrations.
• Mentor teams and set standards for AI engineering and cloud-native development.
• Collaborate with product, engineering, sales, and partners to accelerate AI adoption.
• Define technical roadmaps, governance, and operating models for large-scale deployments.
• Stay current with emerging AI tech and apply to customer scenarios.

Skills

System design

Python

APIs

Microservices

Cloud-native

GCP

Vertex AI

Agent Builder

LLMs

AI governance

Kubernetes

Data engineering

Tools

Kubernetes

Docker

CI/CD

Cloud architecture

Job description

• Must have 10+ years of software engineering experience with strong expertise in system design

and scalable architecture.

• Must have extensive experience in Python, APIs, microservices, and cloud-native application development.
• Must have 4+ years of hands-on experience with Google Cloud Platform (GCP), Vertex AI, Gemini APIs, Agent Builder,

and AI/ML platforms.

• Must have experience designing and delivering enterprise AI solutions using LLMs, RAG,

multi-agent systems, and Agentic AI frameworks.

• Must have experience leading customer-facing solution architecture, technical consulting,

and executive stakeholder engagements.

• Must have experience building AI accelerators, reusable frameworks, PoCs, and production-grade AI applications.
• Must have expertise in cloud architecture, Kubernetes, containerization, DevOps, CI/CD,

and platform engineering.

• Must have strong experience in data engineering, vector databases, knowledge retrieval systems,

and AI governance.

Roles & Responsibilities

• Lead the solution architecture and technical strategy for enterprise AI and cloud transformation initiatives.
• Engage with customers and business stakeholders to translate business challenges into scalable AI solutions.
• Design and oversee the development of AI-powered applications leveraging Gemini, Vertex AI, and Google Cloud services.
• Build and drive complex AI architectures involving RAG, Agentic AI, multimodal AI, and enterprise integrations.
• Lead technical discovery sessions, workshops, PoCs, and customer demonstrations.
• Mentor engineering teams and establish best practices for AI engineering and cloud-native development.
• Collaborate with product, engineering, sales, and partner teams to accelerate AI adoption and business outcomes.
• Define technical roadmaps, governance standards, and operational models for enterprise-scale AI deployments.
• Stay current with emerging AI technologies and apply them to customer scenarios