We’re Hiring | GCP AI, GenAI & Agentic AI Architect | Pan India We are looking for an experienced AI Solution Architect to lead the design and implementation of enterprise-scale AI, Generative AI, and Agentic AI solutions on Google Cloud Platform (GCP). The ideal candidate will have strong expertise in AI/ML architecture, Generative AI, LLM-based applications, Agentic AI, Google Cloud services, and enterprise solution design. This role will involve working closely with customers, business stakeholders, engineering teams, and leadership to translate business requirements into scalable, secure, and production-ready AI solutions.

Location: Pan India

Experience: 8+ Years in Data / ML / Cloud Architecture, including 3+ years of experience in AI/GenAI solution design

Employment Type: Full-time Key Responsibilities

Design and lead end-to-end AI and Generative AI architectures on Google Cloud Platform (GCP).

Architect scalable AI/ML platforms leveraging Google Vertex AI and other relevant GCP services.

Define architecture for model training, fine-tuning, deployment, inference, monitoring, and lifecycle management.

Design and implement LLM-powered enterprise applications using modern Generative AI patterns.

Architect Retrieval-Augmented Generation (RAG) solutions, including document ingestion, chunking, embeddings, vector search, retrieval, and response generation.

Design prompt orchestration and management strategies for LLM-based applications.

Implement and architect tool/function calling capabilities for LLM applications.

Evaluate and define multi-model strategies, selecting appropriate foundation models based on business requirements, cost, latency, performance, and use case.

Design Agentic AI systems involving task-oriented agents, planners, tool usage, memory, decision-making, and autonomous workflows.

Architect multi-agent and agent-based solutions for complex enterprise business processes.





Ensure AI solutions are designed for scalability, reliability, security, performance, and cost optimization.

Pre-Sales & Client Engagement

Lead AI/GenAI discovery workshops with customers and business stakeholders.

Understand customer business challenges and translate them into AI/GenAI solution architectures.

Support RFPs, RFIs, proposals, solution presentations, and technical estimations.

Create architecture diagrams, technical proposals, solution blueprints, and proof-of-concept approaches.

Present AI/GenAI solutions to senior leadership and CXO-level stakeholders.

Collaborate with sales, consulting, engineering, and delivery teams to ensure alignment between proposed architecture and implementation.

AI Governance & Responsible AI

Define and implement AI governance frameworks and responsible AI practices.

Establish appropriate AI safety guardrails, security controls, and access controls.

Design solutions for model observability, monitoring, evaluation, and performance tracking.

Address enterprise requirements related to data privacy, compliance, security, risk management, and regulatory requirements.

Define processes for monitoring model quality, hallucinations, bias, latency, cost, and overall application performance.

Mandatory

Skills

8+ years of experience in Data, ML, Cloud, or Solution Architecture.

3+ years of hands-on experience in AI/GenAI solution architecture or design.

Strong expertise in Google Cloud Platform (GCP).

Hands-on experience with Google Vertex AI.





Strong understanding of AI/ML model training, deployment, inference, and lifecycle management.

Strong experience designing LLM-based applications.

Hands-on understanding of RAG architectures.

Experience with prompt orchestration and tool/function calling.

Understanding of multi-model LLM strategies.

Strong knowledge of Agentic AI architectures, task-oriented agents, planners, and autonomous workflows.

Experience designing enterprise-grade AI solutions with focus on scalability, security, performance, and reliability.

Strong client-facing and stakeholder management skills.

Experience in pre-sales, discovery workshops, RFPs, and executive-level presentations.

Good understanding of AI governance, responsible AI, model observability, and compliance. Positive to Have

Google Cloud Professional Machine Learning Engineer certification.

Google Cloud Professional Cloud Architect certification.

Experience with advanced Vertex AI capabilities and GenAI services.

Exposure to multi-agent architectures and enterprise AI platforms.

Experience integrating AI solutions with enterprise applications and APIs.

Knowledge of cloud-native architecture, microservices, APIs, and event-driven architectures.

Ideal

Candidate The ideal candidate is a hands-on AI Solution Architect and client-facing technology leader who can bridge the gap between business requirements and technical implementation.

You should be equally comfortable designing an enterprise GenAI architecture, discussing technical trade-offs with engineering teams, conducting customer discovery sessions, and presenting solutions to CXO-level stakeholders.

If you have experience building production-grade AI, GenAI, and Agentic AI solutions on GCP and can lead architecture from discovery through delivery, we would like to hear from you.

📌 GCP AI, GenAI & Agentic AI Architect (Bengaluru)
🏢 Berribot
📍 Bengaluru