AI Platform Lead

About the Role:

We are looking for an AI Platform Lead to build and scale the enterprise AI platform that enables teams across the organization to develop, deploy, and operate AI solutions securely and efficiently.

This role will own the platform architecture, roadmap, and delivery of shared AI capabilities, including model serving, model routing, RAG and knowledge services, agent orchestration, evaluation, observability, governance, and cost management.

The ideal candidate is a hands-on technical leader who can combine deep AI platform expertise with strong engineering discipline, practical security awareness, and the ability to work with senior stakeholders, product teams, data teams, and enterprise technology functions.

What You Will Do:

• Define and deliver the enterprise AI platform roadmap, architecture, standards, and operating model.
• Build reusable platform capabilities for model cataloging, model serving, model routing, RAG, agent orchestration, evaluation, observability, and token/cost management.
• Enable teams to discover, evaluate, deploy, and consume commercial and open-weight AI models through secure, standardized services.
• Establish governance and controls for model use, data access, agent autonomy, tool integration, auditability, and responsible AI operations.
• Lead engineers and partner with product, data, security, legal, compliance, and architecture teams to accelerate safe AI adoption across the enterprise.
• Drive platform reliability, performance, scalability, cost efficiency, and developer experience.

What We Are Looking For:

• Strong experience designing, building, and operating production AI/ML, generative AI, or platform-engineering capabilities at enterprise scale.
• Deep understanding of foundation models, model serving, inference architecture, model evaluation, RAG, embeddings, vector or hybrid search, and LLMOps/MLOps practices.
• Hands-on experience with modern engineering practices, including Python, APIs, Kubernetes, cloud-native platforms, CI/CD, observability, and secure operations.
• Practical knowledge of AI agents, tool calling, workflow orchestration, human-in-the-loop controls, or agentic architectures.
• Strong leadership skills, with the ability to guide senior engineers, make architectural trade-offs, influence stakeholders, and communicate complex technical topics clearly.

Preferred Experience

• Experience with platforms or tools such as PyTorch, Hugging Face, vLLM, TensorRT-LLM, Triton, Ray, MLflow, OpenTelemetry, LangGraph, Semantic Kernel, AutoGen, CrewAI, or similar technologies.
• Experience with open-weight model ecosystems, fine-tuning or adaptation methods, model optimization, enterprise knowledge platforms, or AI security controls.
• Experience building internal developer platforms, AI enablement platforms, or enterprise-grade shared technology services.

Why This Role Matters

This is a high-impact leadership role for someone who wants to shape how AI is adopted across a large enterprise. You will create the platform foundation that turns AI experimentation into trusted, reusable, production-grade capabilities.