Job Description

GenAI Cloud Architect JD

Key Responsibilities:

• Platform Architecture & Design
• Define and evolve the reference architecture for the AMS/IMS/ADM platform leveraging Agentic AI frameworks such as AutoGen, LangGraph, and LangChain
• Architect multi-agent orchestration capabilities including dynamic process planning, human-in-loop workflows, and autonomous decision-making
• Ensure modular, scalable, and secure architecture that supports multi-tenancy, RBAC, and hybrid cloud deployments (Azure/AWS/GCP)
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• Agentic AI Integration
• Design and implement agentic runtimes capable of orchestrating single/multi-agent workflows with capabilities like memory, feedback loops, and long-term learning
• Integrate AI-driven features such as predictive incident management, self-healing systems, and autonomous knowledge management
• Delivery Excellence & Optimization
• Embed AI capabilities to automate QA, predictive maintenance, SLA governance, and intelligent workload allocation
• Drive continuous learning and optimization by leveraging real-time telemetry and historical data to refine models and processes
• Security, Compliance & Governance
• Ensure platform compliance with global standards (e.g., EU AI Act, HIPAA, PCI DSS) and implement mechanisms for content safety, prompt injection prevention, and audit logging
• Lead regular bias audits and ethical reviews of AI models and data pipelines.

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• Collaboration & Leadership
• Collaborate with engineering, product, and delivery teams to align platform capabilities with business goals
• Mentor solution architects and engineering leads across AMS, IMS, and ADM domains.
• Engage with stakeholders to define platform KPIs and success metrics.
• Innovation & Roadmap Ownership
• Own the technology roadmap for the platform, including LLM/SLM selection, vector database strategy, and RAG (Retrieval-Augmented Generation) enhancements
• Evaluate emerging technologies and frameworks to continuously evolve the platform’s capabilities.

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• Desirable Skills & Experience:

   

  • Proven experience in architecting large-scale enterprise platforms with GenAI and AIML integration.
  • Good Understanding of AMS/IMS/ADM delivery models and operational workflows.
  • Hands-on experience with LLMs, vector databases, and AI orchestration tools.
  • Strong knowledge of cloud-native architectures, DevSecOps, and observability frameworks.
  • Excellent communication and stakeholder management skills.
  • Good Knowledge on atleast one Cloud between Azure, AWS or Google
  • Understanding on the Services and Components of Cloud

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