MS AI4AI PlatformEngineering Manager KA 560016

EY · Consulting & Professional Services

Bengaluru, India
Hybrid
Posted today
Apply by 19 Oct

About the job

At EY, you’ll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture and technology to become the best version of you. And we’re counting on your unique voice and perspective to help EY become even better, too. Join us and build an exceptional experience for yourself, and a better working world for all.

Job Title: AI Platform Engineering Manager

Role Overview:

EY GDS's Managed Services “AI for AI” team is looking for an AI Platform Engineering Manager to own the deployment, scaling, and reliability of our agentic AI solutions across a complex, hybrid infrastructure landscape — multi-cloud, on-prem, and hosted model environments. You'll lead a team of engineers responsible for turning AI prototypes into resilient, enterprise-grade platforms that run globally, securely, and cost-effectively.

This role sits at the intersection of platform engineering, MLOps/LLMOps, and agentic systems architecture.

Key Responsibilities:

Own platform deployment for agentic AI solutions across AWS, Azure, and/or GCP, as well as on-prem and hybrid-hosted model environments (open-source and proprietary LLMs).

Design and manage CI/CD and MLOps/LLMOps pipelines for model deployment, versioning, rollback, and continuous evaluation at scale.

Architect for scale and resilience — ensuring platforms reliably serve 100,000+ concurrent users globally with strong uptime, latency, and cost-efficiency targets.

Lead a team of platform/infrastructure engineers , setting technical direction, mentoring, and managing delivery timelines.

Partner cross-functionally with AI Engineers, Forward Deployed Engineers, Responsible AI leads, and Product Design to translate agentic workflows into production-ready systems.

Manage model-hosting strategy , including trade-offs between hosted APIs (e.g., Anthropic, OpenAI, Azure OpenAI), self-hosted open-source models, and on-prem deployments for data residency/compliance needs.

Build observability and monitoring for agentic systems — tracing, logging, cost monitoring, drift detection, and performance dashboards.

Drive security, compliance, and governance of AI infrastructure in collaboration with Responsible AI and InfoSec teams, particularly given enterprise/regulated-client contexts (tax, cybersecurity, supply chain data).

Optimize infrastructure cost and performance , balancing GPU/compute resource allocation across cloud and on-prem environments.

Contribute to platform strategy and roadmap , advising leadership on build-vs-buy decisions, emerging tools, and infrastructure investments.

What We're Looking For

Experience

5–8 years in platform engineering, infrastructure/DevOps, SRE, or MLOps roles, with at least 2+ years working on AI/ML or LLM-based systems in production.

Demonstrated experience deploying and scaling software/AI platforms across multiple cloud providers (AWS,Azure, GCP) and in on-prem/hybrid environments.

Experience deploying and managing both hosted LLM APIs and self-hosted/open-source models (e.g., Llama, Mistral) in production.

Experience building or operating agentic AI systems or complex multi-step AI workflows is highly preferred.

Prior experience managing or leading a team of engineers.

Technical Skills

Strong proficiency in Infrastructure-as-Code (Terraform, Pulumi, or CloudFormation).

Hands-on experience with Kubernetes, containerization (Docker), and orchestration at scale.

Experience with CI/CD tooling (GitHub Actions, Jenkins, GitLab CI, etc.).

Familiarity with MLOps/LLMOps tooling

Understanding of model-hosting economics, GPU resource management, and inference optimization techniques (quantization, batching, caching).

Working knowledge of enterprise security, data residency, and compliance requirements in regulated industries.

Proficiency in at least one major programming language (Python strongly preferred; Go or Java a plus)

Soft Skills / Leadership

Proven ability to lead engineering teams in fast-paced, ambiguous, build-from-scratch environments.

Strong cross-functional collaboration skills — comfortable working with Data SMEs, Product, Responsible AI, and business stakeholders.

Clear communicator who can translate technical trade-offs into business impact for non-technical leadership.

Comfortable operating in a "zero to one" environment — building platform foundations rather than maintaining existing ones.

What We Offer:

A leadership position within a globally recognized team at the cutting edge of AI/ML innovation, providing the opportunity to work on transformative projects with significant impact.

Access to an extensive network of professionals and resources across the globe, fostering an environment conducive to continuous learning and career advancement.

A diverse and inclusive culture that celebrates individuality and encourages the expression of ideas, facilitating collaborative team efforts and personal growth.

Comprehensive support and guidance to develop into a transformative leader, equipped to navigate and excel in today's rapidly evolving technological landscape.

EY | Building a better working world

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