Top AI Product Manager Jobs in Chicago, IL

Own the vision, roadmap, architecture, delivery, adoption, and measurement of AI-powered GTM products that improve sales productivity. Partner with sellers, GTM leaders, engineering, data, security, and business systems teams to identify workflow friction, build integrations and automations, launch prototypes and scalable solutions, and establish governance. Measure seller time savings, workflow efficiency, deal progression, adoption, and business impact while ensuring secure, reliable, trusted AI experiences.

Own the vision, roadmap, and delivery of customer-facing AI, predictive analytics, and SaaS data products. Partner with strategic clients, UX, data science, engineering, sales, and marketing to translate business needs into technical requirements, validate product hypotheses, and launch features that drive adoption, retention, and revenue expansion. Use SQL and data visualization tools to analyze data, communicate insights, and shape intuitive product experiences.

The Product Manager will lead AI solution strategy and execution across the Clover ecosystem. Responsibilities include prioritizing AI workflow use cases, translating business processes into agentic experiences, defining metrics and roadmaps, building evaluation and confidence-scoring frameworks, implementing governance and audit workflows, prototyping prompts and agent systems, and partnering with vertical product managers. The role requires extensive product management experience, strong generative AI expertise, analytical execution skills, and hands-on technical prototyping capabilities.

Leads the discovery, development, launch, and scaling of AI-first product capabilities. Translates ambiguous customer problems into hypotheses, requirements, evaluation criteria, roadmaps, and measurable outcomes. Partners with engineering, UX, tax SMEs, go-to-market, and customer success to prototype and operationalize reliable, compliant AI solutions. Owns AI quality, monitoring, performance, feedback loops, responsible AI practices, and continuous improvement while influencing cross-functional stakeholders and mentoring junior product owners.

Own the AI Services product strategy, roadmap, and execution for agentic workflows, MCP tools, connectors, and AI quality infrastructure. Define agent behavior, evaluation frameworks, integrations, metrics, and risk controls while partnering closely with engineering, architecture, security, legal, and consuming product teams. Drive adoption across the portfolio, make technical trade-offs, communicate outcomes to leadership, and deliver reliable AI capabilities for enterprise finance and accounting users.

Lead the end-to-end development of agentic AI products for workforce management, from operational research and agent definition through prototyping, evaluation, enterprise deployment, and commercialization. Define human-in-the-loop controls, tools, escalation rules, specifications, and release criteria. Build prototypes, prompts, evaluation sets, and code contributions while diagnosing model and system failures. Partner with enterprise design customers, engineering, AI Lab, executives, and go-to-market teams to deliver reliable, compliant products.

Own the Field First Mobile App and future AI products from discovery through scaling. Responsibilities include field research, roadmap ownership, content governance, AI instruction and guardrail design, question-bank testing, vendor evaluation, requirements, pilot management, adoption, measurement, and executive reporting. The role partners with IT, HSE, Operations, HR, Fleet, vendors, and frontline leaders to deliver trustworthy AI assistance that improves safety support, onboarding, and operational efficiency.

Own portions of the AI product roadmap for Global Investment Banking, manage platform operations and vendors, evaluate AI features and use cases, and coordinate risk, compliance, legal, and technology reviews. Lead requirements, user acceptance testing, release readiness, training, adoption initiatives, workflow libraries, and value reporting. Provide hands-on expertise in prompts, agent workflows, responsible AI, platform performance, and practical AI applications while influencing cross-functional stakeholders.

Owns the vision and strategy for an AI product area within Salsify’s PXM platform. Leads customer discovery, AI-assisted research, experiments, pilots, prioritization, and product delivery in partnership with engineering and design. Builds cross-functional alignment, communicates with senior leaders and customers, manages trade-offs, and drives adoption and measurable business outcomes. Requires hands-on experience building with LLMs, agents, and AI tools, plus strong product judgment and 5–8 years of product management experience.

Own the product roadmap for AI-powered insurance customer experiences, translating strategy into shipped capabilities. Responsibilities include stakeholder and demand management, problem framing, success-metric definition, data-driven analysis, user experience collaboration, prioritization, and cross-functional execution. The role also involves experimenting with Generative AI and agentic technologies and responsibly scaling successful concepts into production.

Lead the roadmap for an enterprise AI platform supporting reusable agent infrastructure, context capabilities, deployment patterns, evaluation, observability, governance, and feedback loops. Partner with Data Science, Engineering, and product builders to prioritize platform investments, manage delivery tradeoffs, drive adoption, measure impact, and establish reliable AI development standards across Kroger Precision Marketing.

Own the vision, strategy, and roadmap for MongoDB’s Partner Platform, including its Partner API, self-service onboarding, enterprise controls, billing, discovery, and partner-managed experiences. Translate partner and customer needs into scalable product capabilities, establish operating models and metrics, and collaborate across engineering, security, IAM, billing, design, marketing, and partnerships. Lead platform adoption for human and AI-agent developers while representing MongoDB externally and driving ecosystem growth.

Owns an AI agent from customer discovery through production launch and roadmap development for credit unions. Responsibilities include rapid prototyping, customer and executive engagement, enterprise implementations, reusable integrations with core banking, loan origination, and CRM systems, product go-lives, launch sequencing, and transition to scaled operations. The role requires strong product judgment, B2B enterprise experience, hands-on AI work, customer presence, persuasive communication, and approximately 20% travel.

Own end-to-end strategy, roadmap, delivery, adoption, safety, and commercial readiness for AI-native cybersecurity products. Conduct customer and partner discovery, lead 0-to-1 launches, define experimentation and evaluation frameworks, and collaborate with engineering, design, sales, finance, and executives. The role requires hands-on LLM product expertise, strong judgment in ambiguous environments, and a focus on trusted AI experiences for security professionals and MSP/MSSP partners.

Own the vision, strategy, and roadmap for an AI evaluations platform supporting offline and online evaluation, production monitoring, agentic testing, SME workflows, and quality dashboards. Partner with applied scientists, engineers, product teams, legal experts, and executives to define evaluation standards, calibrate LLM judges, assess build-versus-buy decisions, and help teams measure and improve AI performance.

Own the post-order product roadmap, improving communications, ticket delivery, AI-powered self-service, agent-assist tooling, customer satisfaction, contact rate, and cost to serve. Partner with Fan Operations, Engineering, Data, Trust & Safety, and Supply to deliver measurable outcomes. Use SQL and analytics to identify customer friction and guide product improvements across marketplace support and ticket fulfillment experiences.

Own Flodesk’s AI product behavior and quality systems across prompt creation, agentic editing, and future marketing workflows. Develop and version prompts, define context and acceptance criteria, build evaluation datasets and rubrics, monitor quality, review traces, diagnose failures, and establish release gates. Translate research, analytics, support feedback, and production issues into priorities and experiments while partnering with engineering, design, marketing, copy, and product teams.

Owns the strategy, prioritization, requirements, launch, adoption, and continuous improvement of AI-enabled products. Translates ambiguous healthcare, clinical, operational, and business needs into product roadmaps, PRDs, KPIs, and execution plans. Partners with engineering, data, security, compliance, legal, clinical, and operations teams to deliver responsible, secure, compliant, and measurable AI solutions.

Own Litify’s AI Call Intelligence product line end to end, including call capture, transcription, summaries, conversational insights, voice agents, and agentic workflows. Define the roadmap, quality standards, guardrails, and evaluation practices; lead client discovery, beta programs, competitive research, backlog prioritization, and cross-functional delivery. Partner with engineering, design, data science, and go-to-market teams to launch products, drive adoption, and measure outcomes.

Own the strategy, development, launch, and performance of a new AI wedding product from zero to one. Responsibilities include defining the roadmap, market positioning, trustworthy AI behaviors, rapid prototyping, user testing, measurement, unit economics, and use of proprietary marketplace and behavioral data. The role also partners with executive, engineering, design, marketing, and data science leaders to shape company-wide AI direction.

Own product direction for AI-native capital-markets operations. Translate operator and issuer needs into technical requirements, build self-serve workflows, extend the platform into new transfer-agent processes, and add real-time visibility, controls, approvals, and audit trails. Deploy human-in-the-loop AI to reduce manual effort while maintaining correctness in regulated workflows. Collaborate with engineering and multiple market participants without direct people management.

Lead the roadmap and delivery of an AI data platform supporting internal teams and external healthcare products. Manage ML and LLM platform workstreams across data ingestion, training, deployment, monitoring, and workflow optimization. Partner with AI engineers, researchers, data scientists, clinical leaders, and business stakeholders to define requirements, develop user stories, validate model performance, and turn proofs of concept into scalable production capabilities.

Own Demandbase’s AI product adoption and growth strategy, guiding customers from discovery and activation through repeat usage, cross-capability adoption, consumption growth, retention, and commercial expansion. Define adoption funnels, meaningful value metrics, lifecycle strategies, experiments, packaging, entitlements, and monetization mechanics. Partner with Product, Analytics, Data Science, Finance, Sales, Customer Success, and Marketing to improve AI outcomes, establish behavioral insights, and turn successful experiments into scalable product experiences.

Own the vision, roadmap, and launch of a new AI-focused CI/CD product. Drive the product from internal system to customer offering through user research, design partners, developer experience, positioning, pricing, and cross-functional leadership. The role requires deep understanding of agent-driven software development, CI systems, technical product tradeoffs, and early-stage product development.

Own the person-data product portfolio, including accuracy, coverage, freshness, compliance, entity resolution, and privacy. Build the AI evaluation system for agent-generated records using golden sets, thresholds, human adjudication, precision, recall, and drift monitoring. Lead the transition from deterministic rules to agent-based processing, collaborate with engineering and data science, prototype in code, and drive cross-functional roadmap execution.