Live opening · Posted 3 days ago

AI Architect

Tata Consultancy Services Limited · Bengaluru, Karnataka, India (On-site)
Linkedin No
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At a glance

The key details from the original listing.

Posted 3 days ago
CompanyTata Consultancy Services Limited
LocationBengaluru, Karnataka, India (On-site)
Work modeNo
SourceLinkedin
Listed3 days ago

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About the role

Description supplied by the original job listing.

Job Title: AI Architect
Location: PAN INDIA
Experience Required: 8 to 15 Years
Role Overview: We are seeking a visionary AI Architect with 8–15 years of experience to lead the strategic design and implementation of enterprise-scale AI solutions. This role requires deep expertise in Generative AI, Agentic AI, and Responsible AI, along with a strong foundation in AI architecture, solution assessment, and cloud-native AI platforms. The AI Architect will define the roadmap, assess existing systems, and guide cross-functional teams in building scalable, secure, and ethical AI systems.
Key Responsibilities:
🔷 Strategy & Roadmap
Define and drive the AI strategy, aligning with business goals and innovation priorities.
Develop and maintain the AI solution roadmap, including short-term deliverables and long-term vision.
Evaluate emerging AI trends and technologies to inform strategic direction.
🔷 Architecture & Design
Architect end-to-end AI solutions using Gen AI, Agentic AI, LLMs, and multi-modal AI.
Design intelligent agent systems using LangChain, LangGraph, Model Context Protocol (MCP), and Agent to Agent Protocols.
Establish scalable and modular AI architectures that support RAG pipelines, Vector DBs, and Embeddings.
Define and enforce AI governance frameworks, including Responsible AI, GuardRails, and compliance with AI Ethics & Regulations.
🔷 Assessment & Optimization
Conduct technical assessments of existing AI/ML systems, models, and data pipelines.
Identify gaps, risks, and opportunities for modernization or enhancement.
Recommend architectural improvements and integration strategies for legacy systems.
🔷 Deployment & Integration
Lead deployment of AI models using Docker, Kubernetes, and MLOps best practices.
Integrate AI solutions with enterprise platforms and cloud-native services (Azure, AWS, GCP).
Ensure performance, scalability, and security of deployed AI systems.
🔷 Leadership & Collaboration
Collaborate with product owners, data scientists, engineers, and business stakeholders.
Mentor engineering teams and contribute to talent development in AI and ML domains.
Represent AI architecture in enterprise governance forums and technical councils.
Must-Have Skills:
Generative AI (Gen AI), Agentic AI
AI Strategy, Architecture, and Roadmap Planning
Python Programming
AI Frameworks (LangChain, AutoGen, CrewAI and LangGraph)
Model Context Protocol (MCP), Agent to Agent Protocol
GuardRails, AI Ethics and Regulations
Prompt Engineering, Responsible AI
Distillation, RAG, Fine-tuning
Multi-modal AI, LLMs
Vector Databases, Embeddings
GenAI deployment tools (Docker, Kubernetes)
AI Solution Assessment and Optimization
Experience with any of the following Cloud Native AI Services:
Azure AI: Foundry, Agents, Search, Bot Services
AWS: Bedrock, Amazon Q, Amazon SageMaker
Google Cloud Platform (GCP): Vertex AI, Model Garden, Agentspace, Cloud Run , GKE, Agent Engine , Compute Engine
Qualifications:
Bachelor’s or Master’s degree in Engineering or Technology.
8+ years of experience in AI/ML solutioning, with at least 3 years in architectural roles.
Proven track record of delivering enterprise AI solutions at scale.
Strong understanding of AI lifecycle, MLOps, and cloud-native architectures.
Excellent communication, stakeholder management, and leadership skills.

Work arrangement
No

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