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Artificial Intelligence Architect - GEN AI /Agentic AI

Artificial Intelligence Architect - GEN AI /Agentic AI

Datamatics

12 - 18 years

50 - 60 Lacs

hyderabad bengaluru mumbai (all areas)

Posted:2 days ago| Platform:

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Skills Required

artificial intelligence cloud generative ai poc ai solutions aiml rag architectural design llm solution design agentic ai technical architecture

Work Mode

Work from Office

Job Type

Full Time

Job Description

Datamatics is a CMMI Level 5 company. Datamatics, a global Digital Solutions, Technology, and BPM Company, provides intelligent solutions for data-driven businesses to increase productivity and enhance the customer experience. With a completely digital approach

Job Role - AI Architect - Gen AI , Agentic AI

location - Mumbai, Bangalore, Hyderabad

Work Mode - WFO

Experience -10+ Years

The AI Architect will lead design and delivery of AI solutions, with a strong focus on Generative AI, large language models (LLMs), AI agents, and core machine learning. The role combines architecture, hands-on prototyping, and close collaboration with business and engineering teams to turn AI opportunities into scalable, production-grade solutions.

Key responsibilities

Define AI/ML architecture and standards, and guide teams on best practices across the AI portfolio.
Design end-to-end AI solutions, including agentic workflows, RAG systems, and ML models, that integrate with existing enterprise platforms.
Lead technical design reviews, PoCs, and reference implementations for AI agents, LLM use cases, and MLOps pipelines.
Collaborate with product, data, and engineering teams to translate business requirements into AI solution designs and roadmaps.
Support presales/RFPs with solution architectures, effort estimates, and implementation plans when required.
Mentor engineers and data scientists on AI architecture, coding standards, and operationalization of models.

Core skills

AI agents and agentic workflows (tool use, orchestration, and integration with APIs and enterprise systems).
LLM and RAG architecture, vector databases, and evaluation of model quality and reliability.
Cloud-native design, microservices, and containerization (e.g., Docker/Kubernetes) for AI workloads.
Strong Python skills and familiarity with common AI/ML libraries and data engineering tools.

enterprise-scale AI solutions

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Artificial Intelligence Architect - GEN AI /Agentic AI