GenAI Cloud Architect

The candidate will have responsibilities across the following functions:

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-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 Optimisation:

• Embed AI capabilities to automate QA, predictive maintenance, SLA governance, and intelligent workload allocation.
• Drive continuous learning and optimisation 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 of at least one Cloud between Azure, AWS or Google.
• Understanding of the Services and Components of the cloud.