Description:

Job Summary :

We are seeking a highly experienced AI Solution Architect with deep expertise in designing and delivering production-grade AI and GenAI solutions.

The ideal candidate will have strong hands-on experience with GCP, advanced understanding of cloud architecture, and the ability to translate complex business needs into scalable, secure, and high-performing AI-enabled systems.

This role requires a blend of architectural leadership, technical depth, and strong stakeholder management skills in a multi-customer enterprise environment.

Key Responsibilities :

Business Engagement :

- Engage with business stakeholders to understand functional requirements, technical constraints, and strategic objectives.

- Explain the AI Booster (AIB) and GenAI solution landscape; map capabilities to client needs and use cases.

- Conduct feasibility assessments, solution walkthroughs, and architecture discussions with cross-functional teams.

Architecture & Design :

- Define end-to-end AI, GenAI, and cloud-native solution architectures aligned with organizational design principles and secure-by-design frameworks.

- Develop detailed High-Level Design (HLD) and Low-Level Design (LLD) documents, ensuring adherence to enterprise architecture standards.

- Present architecture recommendations with clear, industry-standard diagrams (C4, UML, sequence diagrams, deployment diagrams).

- Lead architecture reviews and secure approvals from Architecture Review Boards and Design Authorities.

Security & Privacy Alignment :

- Collaborate closely with Security, Compliance, and Privacy teams to embed security controls, model governance, and data protection requirements into the solution.

- Address security concerns proactively and secure required sign-offs from risk and privacy functions.

Implementation Guidance :

- Work with Platform Engineers, MLOps teams, and cloud engineering teams to support implementation and deployment activities.

- Remain hands-on in evaluating tools, building prototypes, and performing POCs for AI/ML, GenAI services, vector databases, orchestration frameworks, and cloud-native capabilities.

- Review solution delivery for alignment with architecture and performance benchmarks.

Technical Expertise :

:- Deep expertise in AI/ML pipelines, GenAI architectures, LLM integration, prompt engineering, vector search, embedding models, and RAG frameworks.

- Strong hands-on proficiency with Google Cloud PlatformVertex AI, BigQuery, Cloud Run, GKE, Cloud Functions, VPC, IAM, networking, and security services.

- Solid understanding of end-to-end model lifecycle, from data ingestion to deployment and monitoring.

- Working knowledge of multi-cloud ecosystems (AWS, Azure, GCP) and cloud-native services.

- Understanding of DevOps/MLOps processes, CI/CD automation, and infrastructure-as-code tools (Terraform, Cloud Deployment Manager).

Delivery & Stakeholder Management :

- Ensure on-time delivery of architectural artifacts, solution components, and implementation milestones.

- Manage multiple stakeholder groups across business, engineering, security, and platform teams.

- Drive alignment and consensus in multi-customer and multi-vendor environments with effective communication and problem-solving.

- Provide thought leadership and continuously evaluate new AI/GenAI technologies for enterprise adoption.

Required Skills & Qualifications :

- 14+ years of IT experience with a strong focus on AI, ML, and GenAI architecture.

- Proven experience designing and deploying production-grade AI/GenAI solutions.

- Deep hands-on knowledge of GCP and cloud-native architectures.

- Strong understanding of cloud networking, identity, security, and distributed systems.

- Ability to translate business needs into scalable, secure, and modular architectures.

- Experience with POCs, solution engineering, and end-to-end system integration.

- Excellent communication, documentation, and stakeholder management skills