at Relativity in Chicago, Illinois, United States
Job Description
Are you looking to be in a workplace where colleagues inspire one another? Are you interested in competitive and impactful benefits? Do you prefer flexible work arrangements?
AtRelativity, we make software to help users organize data, discover the truth, and act on it. Our e-discovery SaaS platform is used by more than 13,000 organizations around the world to manage large volumes of data and quickly identify key issues during litigation, internal investigations, and compliance projects.
The Product Management team is looking for aSenior Product Manager to lead the product roadmap and success of Relativity's ML Operations and AI Services functions. These teams oversee the AI platform infrastructure and tooling that are used by AI application teams and Data Science teams to design, develop, and operate AI solutions at scale, with a focus on generative AI-powered innovation.
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 closely with your Engineering counterparts to ensure that the team deliversa product that meets our scalability, reliability, usability, observability, efficiency and performance standards.
Be well versed in technical aspects of ML Operations and broader AI tooling such that you can clearly communicate with development team members and make informed decisions about your product. We run an Azure stack with Prefect, Spark, and Databricks but welcome experience with alternative tooling.
Possess the technical acumen needed to understand the challenges faced by our internal customers, including the root cause of production incidents such that you can propose effective solutions for them alongside Engineering.
Cultivate a deep understanding of generative AI technology and large language models with an ability to lead technical conversations... For full info follow application link.
