Role & responsibilities

Senior AI Platform Architect - AI Centre of Excellence (GenAI & M365 Copilot)

Location : Offshore (India) with regular client-facing collaboration across time zones

Experience : 12-15 years (Platform / Cloud Architecture + GenAI delivery)

Role Overview

We are seeking a Senior AI Platform Architect to be a core member of the AI Center of Excellence (AI CoE) . This role combines deep platform and cloud architecture expertise with hands-on Generative AI solution design, M365 Copilot enablement, and cross-functional stakeholder engagement.

The AI Platform Architect will design and deliver enterprise-grade GenAI and Copilot solutions , define technical standards and guardrails, and work closely with the client’s governance anchor and cross-functional teams — including Infosec, Infrastructure, Compliance, and Legal — to ensure AI adoption is secure, governed, and production-ready .

A key aspect of this role is translating governance intent into enforceable architectural controls , and bridging the gap between business enablement goals and responsible AI implementation. This role requires strong communication skills and demonstrated experience working across geographies, business stakeholders, and technical teams in large enterprise settings.

Key Responsibilities

1. AI CoE Architecture Standards & Guardrails

- Establish governance-by-design practices including auditability, access control, prompt logging, and AI lifecycle management.
- Translate governance and compliance requirements — provided by the client’s governance anchor — into enforceable technical controls and standard architectural patterns .
- Contribute to reducing fragmented guardrails and shadow AI usage across the enterprise by defining explicit adoption pathways and intake standards.





- AI Policy & Governance Collaboration

- Work alongside the client’s governance lead to assess existing AI-related policies, standards, and controls across cloud platforms, data tools, GenAI / Copilot SaaS tools, and developer platforms.
- Identify gaps between policy intent and platform-level enforcement; translate findings into concrete architectural recommendations.
- Produce governance artifacts including architecture decision records, control mapping documents, and standards documentation that bridge technical design and compliance requirements.
- Support AI policy refresh and ensure alignment between updated policy intent and implementable technical guardrails.

- AI Intake, Review & Decisioning Support

- Support the operationalization of a structured AI intake and approval workflow, including standardized risk, security, and value assessment templates.
- Define technical “definition of done” criteria for AI initiatives covering security review, data classification, model risk controls, and production readiness.
- Partner with governance and compliance stakeholders to document and manage exceptions and risk acceptance in line with CoE standards.

- Enterprise Security, Data & Platform Governance

- Embed security-by-design and Responsible AI principles into GenAI architectures.
- Ensure AI solutions align with enterprise standards for:

- Data protection, classification,



and sensitivity labeling (Microsoft Purview, M365 E5)
- Identity, access control, and least-privilege principles (Entra ID, CyberArk)
- Zero Trust alignment and network-layer AI governance
- Auditability, compliance logging, and regulatory alignment
- Advice on third-party AI vendor and SaaS tool evaluations, including data processing risks, model provenance, and contract-level data protection implications.

1. GenAI Solution Architecture
- Design and deliver production-grade GenAI solutions including:

- Retrieval-Augmented Generation (RAG) and knowledge grounding patterns
- Agentic and multi-step AI workflows
- Enterprise copilots and AI assistants
- Define patterns for prompt orchestration, hallucination control, evaluation pipelines, and LLMOps observability (model monitoring, prompt drift, cost attribution, incident response).
- Guide teams on build vs. buy decisions for GenAI platforms and tooling.
- Review and approve solution designs prior to production deployment, ensuring alignment with CoE standards .
- (Good to have) Architect M365 Copilot deployments including Copilot Studio extensions, Graph connectors, and plugin integrations .

1. Stakeholder Engagement & Cross-functional Collaboration
- Act as the primary technical interface between the AI CoE and cross-functional teams including Infosec, Infrastructure, Compliance, Legal, and Business Enablement.
- Communicate architectural positions and governance recommendations clearly to both technical teams and senior non-technical stakeholders.
- Collaborate across geographies with distributed client teams; adapt communication style and engagement model to different stakeholder contexts.
- Represent the CoE in architecture review boards,

📌 Architect (Bengaluru)
🏢 sonataOne
📍 Bengaluru