GenAI Cloud Architect (Exponential)

The core responsibilities for the job include the following:
Platform Architecture and 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-the-loop workflows, and autonomous decision-making.
Ensure modular, scalable, and secure architecture that supports multi-tenancy, RBAC, and hybrid cloud deployments (Azure/AWS/GCP).
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 and 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, and 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.
Collaboration and 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 and 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.
Requirements:
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 the Services and Components of the cloud.

Experience
10-14 yrs