CTO - Technical Architect

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)

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.

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.

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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Applications from people with disabilities are explicitly welcome.