Overview
Lead enterprise AI systems architecture strategy across the Generative AI platform stack. Shape architecture standards, modernization priorities, governance, and scalable cloud designs for secure, resilient, compliant AI systems.
What you'll do
- Drive enterprise-wide AI architecture strategy across shared services, orchestration, model integration, APIs, data flows, and downstream systems.
- Define reference architectures, design standards, integration patterns, and cloud approaches.
- Lead architecture decisions for AWS, Azure, and Google Cloud or hybrid AI environments.
- Establish reusable patterns for RAG, model serving, prompt orchestration, agentic AI, gateways, and service integration.
- Lead governance forums and review major solution designs and technical trade-offs.
- Partner with business, product, engineering, cloud, security, risk, data, and operations teams.
- Mentor architects and engineering leaders and represent Architecture in senior forums.
What you'll need
- 12–17 years of experience in solution, enterprise application, platform, or AI/ML architecture.
- Bachelor's degree in Computer Science, Computer Information Systems, Engineering, Mathematics, or a related discipline.
- Hands-on experience with Generative AI, LLMs, ML systems, RAG, vector databases, prompt orchestration, and AI integration.
- Expertise in AWS, Azure, or Google Cloud Platform architecture.
- Experience with cloud-native architecture, APIs, microservices, distributed systems, event-driven patterns, and platform design.
- Knowledge of AI governance, Responsible AI, model risk, compliance, testing, security, and production controls.
- Understanding of DevSecOps, CI/CD, observability, reliability engineering, and platform engineering.
Nice to have
Details
- Location: Bangalore, India.
- Work mode: On-site.
- Role level: Vice President.
Read the full description and apply on the company’s own careers page.
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