Sr Manager AI Platforms

What You'll Be Doing

• Own and evolve the enterprise AI/ML platform strategy, including AI/ML platform capabilities, GenAI tooling, agent frameworks, and shared services
• Define and maintain a clear platform roadmap that aligns business priorities with scalable, secure, and reliable technical capabilities
• Drive the maturation of AI/ML platforms from early enablement to enterprise-scale, production-ready systems
• Partner with engineering teams to:
• Translate business and product needs into platform capabilities and standards
• Define architecture patterns, guardrails, and best practices for AI/ML development and deployment
• Collaborate with product managers and business stakeholders to:
• Enable faster experimentation while ensuring production readiness
• Balance short-term delivery needs with long-term platform sustainability
• Prioritize platform initiatives based on enterprise impact, risk reduction, adoption, and ROI
• Establish and track platform success metrics, including adoption, reliability, performance, cost efficiency, and developer productivity
• Partner with Security, Privacy, and Compliance teams to ensure responsible AI, access controls, and governance are built into the platform
• Manage vendor and partner relationships (e.g., cloud providers, AI platforms) to ensure optimal use of external technologies
• Communicate platform vision, roadmap, and progress clearly to technical and non-technical stakeholders

Basic Qualifications

• Bachelor’s degree in Computer Science, Engineering, Data Science, Information Systems, or a related field, or equivalent work experience.
• 8+ years of experience in platform management, product management, technology leadership, software engineering, data engineering, AI/ML engineering, or infrastructure leadership.
• 4+ years of experience working with AI/ML platforms, MLOps, GenAI systems, model lifecycle management, or ML infrastructure in an enterprise environment.
• 2+ years experience with Databricks and cloud AI platforms such as Azure, Google Cloud Platform, or AWS.
• Experience owning or delivering shared platforms, reusable services, or infrastructure capabilities used by multiple teams.
• Strong understanding of AI/ML development lifecycle, including experimentation, deployment, monitoring, model governance, and operational support.
• Experience working in agile delivery models and cross-functional technology environments.
• Strong communication skills, with the ability to translate complex technical concepts into clear business and executive-level narratives.
• Proven ability to partner with engineering, architecture, security, product, and business teams to deliver enterprise technology capabilities.

Preferred Qualifications

• Experience with GenAI platforms, large language models, agentic AI frameworks, prompt orchestration, vector databases, retrieval-augmented generation, or AI application development patterns.
• Experience with Databricks, MLflow, Feature Store concepts, model serving, model monitoring, CI/CD, observability tools, and cloud-native infrastructure.
• Strong understanding of scalability, reliability, resiliency, observability, access controls, and cost management for enterprise platforms.
• Experience defining and enforcing platform standards, APIs, reusable patterns, governance models, and engineering best practices.
• Experience with responsible AI practices, model risk management, privacy controls, and enterprise AI governance.
• Able to break down complex platform challenges into clear, iterative, deliverable capabilities.