Top AI Product Manager Jobs in Chicago, IL

Own the roadmap and delivery of legal AI and platform initiatives across ServiceNow’s legal technology portfolio. Design, prototype, evaluate, and launch trusted AI agents for legal workflows, measuring productivity and business impact. Translate stakeholder needs into product requirements, prioritize backlogs, define evaluation criteria, and partner with Engineering and Product teams to improve internal solutions and potentially inform customer-facing releases.

Leads the AI automation product vision and roadmap for disability claims operations. Prioritizes AI and RPA opportunities, designs human-in-the-loop workflows, manages confidence and escalation controls, and aligns product strategy with engineering and operations. Directly manages and develops Product Owners across AI, analytics, foundation, and RPA teams while communicating business value and delivery trade-offs to senior leaders. Drives measurable operational transformation using agentic AI, LLMs, and scaled agile delivery.

Drives revenue and profitability for Cisco AI infrastructure products by managing pricing, promotions, positioning, vendor relationships, SKUs, e-commerce merchandising, forecasts, and marketing plans. Serves as the product portfolio subject matter expert, identifies emerging technologies, manages vendor co-op funding, analyzes market opportunities, and develops annual business plans while coordinating with segment marketing and internal stakeholders.

Own Auth0’s AI product strategy and roadmap, focusing on secure identity and access for AI agents. Define and launch 0-to-1 products, translate customer and developer needs into technical requirements, manage engineering backlogs, and validate prototypes. Apply AI and identity standards including MCP, OAuth, OIDC, SAML, and mTLS. Partner cross-functionally with engineering, design, security, marketing, developer relations, and sales to drive launches and adoption.

Own the strategy, roadmap, and execution for Okta’s AI agent identity products. Define capabilities for agent authentication, delegated authorization, dynamic permissions, lifecycle management, and auditability. Partner with engineering, design, architecture, and stakeholders to launch secure, scalable features based on OAuth/OIDC and emerging AI frameworks. Engage customers, monitor market trends, analyze product data, and support marketing and technical sales as the AI identity subject matter expert.

Own the full lifecycle of enterprise AI products, from discovering and validating use cases through MVP development, scaling, and broad adoption. Build AI-native experiences including agents, copilots, and workflow automation. Define quality metrics, evaluate AI performance, and drive adoption across IT, HR, Finance, and go-to-market teams. The role requires strong product leadership, experience shipping AI/ML products, and the ability to balance experimentation with reliable enterprise execution.

Own Deepgram’s AI applications product line, including strategy, roadmap, customer definition, acquisition, activation, retention, monetization, and profitability. Lead zero-to-one product development, represent the product with customers and partners, and coordinate research, engineering, design, and marketing. Prototype and validate ideas through real usage and measurement while communicating decisions to executives. The role requires shipped, paid consumer or prosumer products, deep AI application experience, technical depth, design judgment, and strong product leadership.

Own internal AI and automation products that make Engine’s business functions faster and more scalable. Map workflows, identify high-value repetitive workloads, establish baseline metrics, partner with engineering to build and launch solutions, and drive adoption. The role requires evaluating LLMs and agents, incorporating human review, controlling scope and costs, measuring cycle-time improvements, and transitioning successful workflows to functional owners.

Own the customer-facing Superhuman experience and Console, including live conversations, builder tools, self-serve activation, analytics, personalization, and weekly releases. Partner with design, engineering, and leadership to improve time-to-value, retention, and customer outcomes. Lead product decisions across web, voice, and video experiences while enabling customers to create, tune, test, and measure AI-powered revenue teammates independently.

Own the vision, roadmap, quality standards, and adoption strategy for catalog APIs powering AI commerce experiences. Lead catalog coverage, product identity, enrichment, ingestion, pricing, availability, freshness, data rights, partner onboarding, metrics, and evaluation initiatives. Partner with engineering, applied science, legal, privacy, security, marketing, and external partners to prioritize investments, guide large senior teams, and scale externally consumed commerce data platforms.

Drive the product vision for Modular's cloud compute platform, collaborating with teams to enhance AI service capabilities and customer engagement.

Lead NVIDIA’s AI for Quantum product strategy, roadmap, and go-to-market initiatives. Translate AI and quantum research into scalable platforms, developer tools, APIs, libraries, and workflows. Partner with researchers, engineers, quantum hardware companies, institutions, and developers to identify applications across quantum design, control, calibration, error correction, and algorithms. Evangelize the platform through technical communications, identify new AI, HPC, and quantum opportunities, and present product strategy to executives.

Own the strategy, roadmap, and delivery of AI-powered capabilities across Mapbox Maps. Partner with engineering, customers, and cross-functional teams to identify use cases, prioritize development, validate solutions, and launch products. Manage pricing and packaging, sales enablement, marketing, trials, and partnerships while driving customer adoption, business growth, and scalable experiences for developers and end users.

Defines LTK’s AI product vision and strategy across agent infrastructure, LLM evaluation, machine learning models, and knowledge graphs. Partners with ML, data science, engineering, and product teams to establish model requirements, evaluation frameworks, launch criteria, and responsible AI practices. Owns trade-offs involving quality, reliability, latency, cost, privacy, transparency, and human oversight while influencing senior leaders and driving AI-powered products for creators, brands, and consumers.

As a Sr. AI Product Manager, you'll develop growth strategies, manage customer motions, collaborate with marketing, and influence product direction based on customer insights for AIStor.

Own the AI product roadmap for document extraction, including prioritization, accuracy metrics, model and vendor decisions, capacity planning, tax-year releases, and correction workflows. Partner with AI, engineering, product, UX, QA, tax, finance, sales, and client success teams to define requirements, evaluate model performance, manage costs and latency, and deliver filing-grade structured data.

Own the strategy and outcomes for Mural’s AI Workflows products from concept through launch. Build prototypes, identify valuable collaboration workflows, define product-quality evaluations, guide model and routing decisions, and determine whether to iterate, scale, or stop based on user evidence. Partner with engineering, ML, design, finance, growth, and other teams on reliability, unit economics, data loops, and agentic multiplayer experiences.

Owns product strategy, roadmap, and execution for AI-powered experiences serving home service professionals. Responsibilities include researching workflows, defining requirements, shaping model behavior and user experiences, prioritizing roadmaps, establishing product and AI performance metrics, coordinating launches, and improving products through customer feedback and analytics. The role partners closely with Engineering, Design, Data, Marketing, Sales, Customer Success, Operations, and AI platform teams.

Designs current- and future-state workflows for AI agents across product verticals. The role facilitates discovery, translates business needs into agent-ready requirements and acceptance criteria, identifies human-in-the-loop decisions, establishes reusable workflow standards, partners with UX and engineering, and validates workflows using user feedback, evaluation results, and performance data.

Owns product development for AI-powered audit evidence review software. Responsibilities include gathering requirements, defining and prioritizing features, coordinating Design and Engineering, managing roadmaps and releases, measuring AI quality and business impact, and using product analytics to guide decisions. The role requires shipping LLM-powered features, establishing evaluation frameworks, balancing automation with human review, and delivering measurable customer and business outcomes.

Own the rollout and scale of AI agents and shared AI platform capabilities across Teamworks’ sports technology products. Drive beta-to-general-availability launches, AI-powered workflows, technical standards, integrations, evaluation datasets, regression testing, permissions, usage measurement, packaging, and customer adoption. Partner across product, engineering, and commercial teams to deliver reliable, secure AI experiences handling sensitive athlete data.

Own defined product features and workflows from discovery through launch and post-launch improvement. Create product artifacts, partner with engineering and design, incorporate customer feedback and analytics, manage roadmaps and backlogs, prepare launch plans, and monitor adoption and quality. The role requires cross-functional collaboration, benefits administration domain learning, responsible use of AI-enabled tools, and hands-on technical engagement with engineers, including troubleshooting and scripting for production support.

Lead the strategy, delivery, and continuous improvement of data and AI platforms and products. Translate business goals into requirements, user stories, backlogs, and measurable KPIs. Coordinate agile cross-functional teams, ensure quality and adoption, manage client and executive stakeholders, surface risks, and drive alignment. The role owns product workstreams within consulting engagements and requires strong data and AI platform knowledge, consulting experience, and significant end-to-end product ownership.

Own the agent orchestration platform and co-lead AI agent solutions across the insurance lifecycle. Define agent roadmaps, prompts, tools, autonomy tiers, evaluation datasets, governance, rollout gates, observability, and cost controls. Partner with product, engineering, data, and experience teams to translate business needs into agent specifications and measurable outcomes. Establish regression testing, human escalation policies, audit trails, and production quality standards for LLM-powered products.

Own product strategy and multi-year roadmaps for GPU back-end networking. Translate AI workload needs into requirements, lead products through qualification and deployment, coordinate engineering and business teams, influence suppliers, and improve performance, reliability, cost, observability, and launch readiness.