Senior Director, Product Management

MRI Software•Cleveland, OH

11h•Remote

About The Position

We are seeking a Director of Product & Engineering to lead our Data & AI Platforms portfolio, owning end-to-end strategy, architecture, roadmap, and execution for a modern, scalable, and AI-enabled data ecosystem. This leader will transform fragmented data and technology capabilities into a unified, global platform that enables analytics, automation, AI-powered workflows, and ecosystem integration. You will lead Engineering teams and partner closely with Design, GTM, and Customer teams to deliver measurable customer and commercial outcomes while operating at both strategic and hands-on execution depth. This role includes building and leading a high-performing, globally distributed organization of Product Managers and Engineering leaders, and establishing consistent product and engineering operating standards across regions.

Requirements

10+ years in Product Management and/or Engineering leadership, including management of Product Managers and technical teams
Experience owning multi-product SaaS or platform portfolios
Proven ability to operate and influence at the executive level
Strong experience with platform product models and ecosystem thinking
Building data and analytics platforms (data lakes, data warehouses, semantic models, pipelines, reporting)
Strong understanding of APIs, integrations, and platform extensibility
Practical experience applying AI/ML, LLM-based capabilities, RAG systems, and agentic AI in products
Understanding of data governance, semantic models, real-time data, and integration patterns
Track record of delivering complex, scalable SaaS products
Strong data-driven decision making and product metrics orientation
Experience working across global, distributed teams
Experience driving product growth, adoption, and monetization
Ability to develop business cases, pricing strategies, and ROI models
Strong understanding of modern architectures: SaaS platforms, microservices, APIs
Cloud platforms such as Azure (preferred), AWS, or GCP, including data platforms, compute, and distributed systems
Data pipelines, data warehouses, and CI/CD
Clear, direct communicator with strong executive presence
Ability to influence across competing priorities and stakeholders
Strong collaboration and cross-functional leadership skills
Bachelor’s degree required; Master’s degree preferred in Computer Science, Engineering, Data Science, or a related field
Systems thinker who sees platforms, not point solutions
Bias toward action, outcomes, and measurable impact
Comfortable with ambiguity, scale, and transformation
Ability to simplify complex problems into actionable strategy
Raises the bar, delivers results, and develops strong teams

Nice To Haves

Experience with Microsoft Fabric, Snowflake, or Databricks is a strong plus
Comfortable engaging in product architecture and technical trade-offs

Responsibilities

Define and drive the Data & AI platform strategy, aligned to company and product vision
Translate business goals into roadmaps tied to measurable outcomes (adoption, revenue, retention)
Establish a unified data and AI platform, leading the delivery of models, workflows, and capabilities across analytics, APIs, integrations, and AI services
Rationalize fragmented capabilities into a scalable, reusable platform model
Partner to drive technology unification and synergy strategies across regions, time zones, and global workforce environments
Build and evolve core platform capabilities including: Data ingestion, pipelines (ETL/ELT), and real-time streaming APIs, integration frameworks, and partner extensibility
Data models, governance, and metadata/lineage
Analytics, reporting, and reusable data products
Define and execute API and ecosystem strategy, including partner monetization and platform access models
Define and operationalize standardized data packages and distribution models to support global consumption and regional needs
Identify and deliver AI use cases embedded into core workflows (not bolt-ons)
Leverage LLMs, RAG architectures, and agentic AI patterns to improve customer outcomes and internal efficiency
Define and scale AI platform capabilities, including model lifecycle, RAG systems, agent orchestration, data pipelines, and governance
Drive Engineering execution of AI platform services and AI-assisted development practices
Drive high-quality, predictable execution across multiple teams, regions, and time zones
Define and evolve the product and engineering operating model, including team topology, platform vs. product boundaries, and delivery ownership
Implement outcome-driven product and engineering practices across data, AI, and platform workstreams
Ensure consistent delivery standards, tooling, and metrics across teams
Own and standardize the global inventory, packaging, and delivery of data products, ensuring consistent, scalable, and reliable access across regions, time zones, and customer segments
Remove blockers and drive accountability for results
Maintain deep understanding of customer needs, industry trends, and competitive landscape
Lead discovery and validation to ensure products solve high-value problems, clearly articulating value propositions tied to measurable client outcomes
Represent the platform internally and externally through client engagement, thought leadership, and industry presence
Partner with Sales, Marketing, and Customer Success on go-to-market execution
Support pricing, packaging, and monetization strategies for data and platform products
Drive growth of data- and API-based revenue streams
Own or materially influence revenue, adoption, and margin performance of data and platform products
Partner effectively with senior executives across Product, Engineering, and GTM
Communicate strategy, progress, and trade-offs clearly across stakeholders
Represent the platform in executive forums and drive cross-functional alignment
Build, lead, and scale a high-performing, globally distributed organization of Product Managers and Engineering leaders across North America, EMEA, and APAC
Coach teams on strong product thinking, engineering excellence, platform mindset, and execution discipline
Establish a consistent, high bar for product management and engineering practices