Educational Qualification* | Bachelor's or Master's degree in Computer Science, Engineering, Information Technology, Data Science, AI, or related field.
Google Cloud, Vertex AI, AI/ML, Cloud Architecture, or Security certifications preferred. |
Experience Range | 12+ years overall IT experience.
6+ years in Enterprise/Cloud Solution Architecture.
4+ years in AI/ML, GenAI, or Enterprise AI initiatives.
3+ years in Google Cloud Platform (GCP) and Vertex AI.
2+ years designing and delivering Agentic AI/LLM-based solutions. |
Tagline/Tech Stack Snapshot - | Enterprise AI Strategy | Agentic AI | Google Cloud | Vertex AI | Gemini | SAP S/4HANA | Python | APIs | AI Governance | Security | Human-in-the-Loop | Multi-Agent Systems |
Role Summary - (To be filled by Practice /DO) | Lead the Customer's Enterprise AI roadmap and AI platform strategy.
Act as the primary advisor for Google Cloud and Vertex AI adoption.
Define scalable, secure, and governed AI architecture patterns.
Drive Agentic AI use cases across enterprise business functions.
Establish standards for AI governance, integration, security, and operational readiness. |
Primary (Must have skills)* - To be Screened by TA Team | Agentic AI / GenAI Solution Architecture: 4+ years
Google Cloud Platform (GCP) & Vertex AI: 3+ years
Enterprise AI/Cloud Architecture & Solution Design: 6+ years
SAP S/4HANA Integration Architecture, including OData/BAPI/API patterns: 3+ years
Python & AI application architecture: 5+ years
Agent orchestration, tool/API calling & workflow automation: 2+ years
REST APIs / Enterprise Integration Architecture: 5+ years
Security, IAM, service accounts, RBAC & enterprise governance: 4+ years
Human-in-the-Loop, approval workflows, auditability & AI guardrails: 2+ years
Production AI architecture including logging, monitoring, exception handling & resiliency: 3+ years |
Why This Role Matters - New addition (To be filled by Practice /DO) | Drives enterprise-scale AI adoption aligned with the Customer's business objectives.
Establishes a unified AI platform strategy across business functions.
Accelerates value realization from Google Cloud and Vertex AI investments.
Ensures AI solutions are secure, governed, scalable, and production-ready.
Creates reusable AI architecture patterns that reduce delivery timelines and risks. |
What You'll Do/
Job Description of Role* (RNR) - To be Evaluated by Technical Panel (Define it to give more clarity) | Strategy & Advisory
Define and evolve the Customer's Enterprise AI roadmap.
Provide executive-level recommendations on AI investments and platform choices.
Identify and prioritize high-value AI and Agentic AI use cases.
AI & Platform Architecture
Design enterprise-scale Agentic AI and GenAI architectures.
Define reference architectures on Google Cloud and Vertex AI.
Establish standards for LLM usage, grounding, orchestration, and governance.
Architect multi-agent workflows and autonomous decision frameworks.
SAP & Enterprise Integration
Design integrations with SAP S/4HANA using APIs, OData, and BAPIs.
Enable AI agents to securely interact with enterprise applications.
Define integration, data access, and workflow automation standards.
Security & Governance
Define AI security architecture, IAM, RBAC, and access controls.
Establish auditability, compliance, human approvals, and AI guardrails.
Implement responsible AI governance and risk mitigation frameworks.
Delivery & Operations
Define observability, monitoring, logging, and resiliency standards.
Drive production readiness reviews, SIT/UAT support, and deployment governance.
Mentor engineering teams and conduct architecture reviews. |
Soft skills/other skills - To be Evaluated by Hiring Manager (To define how this will be evaluated) | Executive communication and presentation skills.
Strategic thinking and business outcome orientation.
Consultative stakeholder management.
Strong problem-solving and analytical abilities.
Influencing and decision-making without direct authority.
Cross-functional collaboration and leadership.
Mentoring and team enablement capabilities.
Ability to simplify complex technical concepts. |
What Success Looks Like (6 12 Months) -
Expected Outcome | Enterprise AI roadmap approved and aligned with business priorities.
Vertex AI reference architecture established and adopted.
AI governance and security framework implemented.
Reusable Agentic AI architecture patterns defined.
Multiple AI use cases moved from concept to production.
SAP integration framework established for AI-enabled workflows.
Platform adoption increased across business units.
Architecture review and AI delivery governance process operational.
Measurable improvements in delivery speed, reuse, and risk management.
Strong executive confidence in AI platform strategy and execution. |
Secondary Skills (Good to have) | SAP Finance / month-end close process understanding: 2+ years
Google Chat / notification and approval integration: 1+ year
Web application / command-center architecture: 3+ years
CI/CD and cloud deployment architecture: 3+ years
SIT/UAT and enterprise production-readiness planning: 4+ years
Agentic AI risk, governance and control frameworks: 2+ years |
Why Join Us - New Addition | Lead AI transformation for a global enterprise customer.
Shape the customer's long-term AI and Agentic AI strategy.
Work directly with executive stakeholders and business leaders.
Architect cutting-edge solutions using Vertex AI and Google Cloud.
Drive high-impact SAP and enterprise AI innovation initiatives.
Establish enterprise standards and reusable AI platforms.
Influence technology decisions with organization-wide impact.
Be at the forefront of scalable, production-grade Agentic AI adoption. |