Director of Product Management, Industrial AI & Automation

RLCore is building the adaptive optimization layer for industrial automation, and they are seeking a Director of Product Management to lead their product function. The role involves defining product strategy, engaging with customers throughout the product lifecycle, and driving the execution of product development in the industrial AI and automation space.

Responsibilities:

• Own the product roadmap, priorities for real-time optimization agents, integration, and customer-facing deployment tools. Balance short-term customer commitments with long-term platform investments
• Synthesize customer needs, technical constraints, and industry signals into a clear product strategy and roadmap
• Define success metrics across the platform, including learning efficiency, control performance, customer adoption, and business impact
• Lead product discovery with customers throughout the sales, deployment, and post-deployment lifecycle
• Build trusted relationships across process engineers, operators, controls engineers, technical leaders, and executives to deeply understand customer needs
• Conduct customer discovery, site visits, workshops, and product reviews, translating field insights into scalable platform capabilities
• Convert complex operational workflows and customer problems into clear product requirements, user workflows, functional specifications, and product designs
• Partner closely with Engineering and Solutions to define requirements, prioritize work, and deliver high-quality software
• Write detailed product / functional specs, including platform components, APIs, simulation tools, orchestration layers, and user experience
• Validate new capabilities through simulation, customer deployments, and operational feedback, using data to continuously refine the product roadmap
• Drive experimentation, instrumentation, and product analytics to measure system performance, user behavior, and product outcomes
• Define and drive the long-term evolution of the RLCore optimization platform, including optimization agents, orchestration, deployment tooling, observability, integrations, and user experience
• Balance customer-specific requirements with scalable platform investments, reusable product capabilities
• Drive standardization across industries through configurable workflows and platform architecture
• Partner with Engineering to develop reusable platform capabilities, architecture, and tooling that accelerate deployments and expansion into new industrial markets
• Partner with Technical Program Management and Solutions to ensure customer deployments generate scalable product improvements
• Translate deployment learnings into roadmap priorities, automation, and tooling that reduce deployment effort over time
• Collaborate on deployment playbooks, implementation standards, and onboarding workflows that enable repeatable deployments
• Capture customer feedback throughout deployment and early production, ensuring recurring needs become scalable product capabilities
• Partner with Go-to-market, Product Marketing and Engineering to implement early customer deployments and turn insights into product learnings
• Contribute to product positioning, onboarding materials, and customer narratives that translate technical depth into business value

Requirements:

• 10+ years in product management, engineering or applied AI - with a proven track record translating real world needs into shipped software
• Strong technical fluency - you've shipped complex software products and can engage confidently with engineers, operators, researchers, and domain experts
• Experience with industrial automation platforms, SCADA, DCS, PLCs, AI/ML, process optimization, or operational technology (OT)
• Experience leading products through ambiguous 0→1 phases, especially in AI/ML, simulation, control systems, or industrial automation
• Demonstrated ability to synthesize user insight, data, and complexity into product strategy and execution
• Excellent written and verbal communication skills, with the ability to influence both technical and business stakeholders
• Experience working in AI products / Autonomous systems / Industrial Automation software / cloud or on prem hybrid products
• Master's or Bachelor's degree in engineering, computer science, or a related technical field
• Hands-on experience with reinforcement learning, multi-agent systems, or simulation environments
• Experience deploying AI systems in safety-critical environments
• Prior working experience in Industrial water, muni water, food & beverage, oil & gas, petrochemicals, mining, pulp & paper, data centers, semiconductor manufacturing, chemical processing