MS-AI4AI-PlatformEngineering-SeniorConsultant

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Job Title: AI Platform Engineering Senior Consultant

Role Overview:

EY GDS's Managed Services “AI for AI” team is looking for an AI Platform Engineering Senior Consultant 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

• 3-5 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 work with 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.

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