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Cognizant
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GenAI Architect

GenAI Architect

Cognizant

10 years

0 Lacs

chennai tamil nadu india

Posted:3 days ago| Platform:

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Skills Required

ai drive ml python java tensorflow pytorch openai reinforcement workflow aws azure gcp vertex devsecops deployment data governance collaboration leadership communication agile design reasoning development service metrics latency crm compliance security

Work Mode

On-site

Job Type

Full Time

Job Description

Job Summary

We are seeking a highly experienced Architect with 10 to 15 years of experience. The ideal candidate will have extensive technical expertise in Generative AI The candidate will play a crucial role in designing and implementing innovative solutions that drive business growth and efficiency.

Minimum Qualifications

10+ years of IT experience.

3+ years in AI/ML, with at least 6 months in

Agentic AI

and

multi-agent systems

Skills & Abilities

Proficiency in Python, Java, C#, or R.
Experience with generative AI frameworks: TensorFlow, PyTorch, LangChain, OpenAI Codex, Claude, Gemini, HuggingFace.
Strong grasp of ML/DL paradigms including supervised, unsupervised, and reinforcement learning.
Familiarity with AgentOps, Agent Observability, and Agent Lifecycle Management
Knowledge of MCP for context sharing and A2A for agent-to-agent communication.
Experience with Shared Memory and Agentic Workflow Orchestration.
Cloud proficiency: AWS, Azure, GCP (especially Vertex AI, Agentspace, ADK).
Understanding of MLOps, AIOps, and DevSecOps for agent deployment and monitoring.
Data governance and ethical AI principles.
Ability to evaluate agentic architectures for deterministic vs autonomous use cases.
Strong collaboration and leadership skills.
Excellent communication and stakeholder engagement.
Familiarity with agile and SDLC methodologies.

Responsibilities

Architect and implement Generative AI and Agentic AI ecosystems using MCP and A2A protocols.
Design modular, scalable agent frameworks with contextual reasoning, shared memory, and multi-agent orchestration
Lead development of domain-specific agents (e.g., Customer Service Agen, Tax Agent, Media Agent, Knowledge Agent) and cross-functional agents (e.g., Orchestrator, Collaboration Agent).
Evaluate agent performance using metrics like time to first token, inter-token latency, and context length.
Collaborate with product and platform teams to embed agents across enterprise workflows (e.g., SDLC, LMS, CRM, ERP).
Ensure compliance with security, privacy, and explainability standards.
Stay ahead of emerging trends in agent marketplaces, agentic proctoring, and autonomous orchestration

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