Role details
Job description
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