Senior Product Manager - ML Ops

In this role, you will:

• Lead product development teams that build AI platform solutions to power RelativityOne’s AI feature set, including aiR for Review, while adhering to Relativity’s AI Principles  
• Evangelize AI platform infrastructure and tooling to drive adoption of generative AI and LLM capabilities (e.g.leveraging GPT-4o) that deliver on product needs and operate at massive scale 
• Oversee AI service procurement with a strategic approach that ensures capacity planning, cost-effectiveness, and the enhancement of broader product capabilities, ultimately driving world-class customer experiences. 
• Build user empathy and a deep understanding of user needs amongst your team and the broader business 
• The ideal candidate will have substantive AI experience, especially in the AI model lifecycle. They will bias towards data and have a strong proficiency in using data to monitor product health, set ambitious goals, and track success. They will passionately advocate for the benefits of our AI platform products and give confidence to the business and our customers that the world’s most powerful AI tooling for Legal Data Intelligence is underpinned by a reliable, highly-efficient, and principled foundation. 

Customer Centric:

• Connect frequentlywith internal customers in Data Science and AI application teams to gain a deep understanding of their day-to-day needs and business goals, in addition to validating solutions with them for feedback in product discovery. 
• Ensure we are solving business problems with the proper balance between delivering on immediate customer needs while also building capabilities that will deliver mid/long-term success. 
• Evangelize to internal AI application teams about the benefits of adopting AI platform components and tooling – be an expert at explaining the “why”. 
• Partner with Engineering in product discovery to build deep alignment on the problems to solve and key results we should target that define success. 
• Act as AI platform SME when external customers have detailed questions about our approach to building and supporting AI products in RelativityOne. 

Product Leadership:

• Own the product roadmap and backlog for your products, with a focus on outcomes we want to achieve over features we want to ship. Solicit feedback from internal SMEs, Engineering, Data Science, Product Managers, and others to drive confidence in decision-making. 
• Own the strategy and vision for your products, ensuring that we are maturing quarterly in each aspect of the ML Ops lifecycle to drive Data Science experimentation and model delivery at scale. 
• Advocate for Relativity’s AI Principles throughout internal decision-making, even when it’s inconvenient or slows us down. 
• Partner with AI service providers like Microsoft to evaluate AI offerings and lead planning on procurement. 
• Possess and apply an in-depth understanding of our AI product suite, giving confidence to teams that our supporting AI technology is informed by the needs of our end users and the strategy of our AI application teams. 
• Set, track, and report on key product metrics that are relevant to your domain and lead decision-making on expected outcomes for product work.   

Technical Leadership

• Work cl