Top AI Product Manager Jobs in Austin, TX

Own execution of Zynga’s internal AI operating platform from intake and triage through release and post-launch measurement. Partner with engineering on complex platform capabilities including chat, knowledge bases, connectors, workflows, and documents. Define requirements, conduct technical research, establish metrics, prioritize requests, unblock delivery, and drive operational rigor across multi-team workstreams.

Own the product strategy and production delivery of shared AI services and infrastructure across 2K. Drive opportunity intake, prioritization, build-versus-buy decisions, roadmap communication, governance, adoption, reliability, cost, latency, and output quality. Partner with engineering, data science, security, trust and safety, and senior leadership to deliver scalable AI capabilities with auditable compliance and measurable business value.

Lead the vision, strategy, and roadmap for AI-native client products, internal tools, data products, and enterprise integrations. Partner with executives, engineering, and data science to evaluate models, data quality, infrastructure, cost, latency, trust, and scalability. Define AI product opportunities, business cases, data requirements, quality standards, and commercial strategies while aligning legal, privacy, trust, and safety stakeholders.

Own the roadmap, backlog, and delivery of data products and an internal data marketplace. Translate stakeholder needs into prioritized requirements, partner with engineering and governance teams, launch reusable and trusted data products, and measure adoption, quality, and business impact. The role also supports AI-enabled data access, external product readiness, documentation, certification, and ongoing product operations.

Own the product strategy and roadmap for SEO and AI visibility across thousands of real estate websites. Lead technical SEO foundations, structured data, performance, experimentation, migrations, measurement, and AI citation visibility. Partner with engineering and product teams to establish scalable defaults, safeguards, acceptance criteria, and reporting that improve organic discovery, client conversions, and platform-wide search quality.

Own Procore’s enterprise AI enablement strategy, roadmap, governance, platform selection, rollout, adoption metrics, and ROI measurement. Partner with IT, engineering, data, and business stakeholders to consolidate AI tools, evaluate vendors, drive change management and training, and make build-versus-buy recommendations. Report progress to executive stakeholders while establishing scalable standards for AI adoption across the organization.

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.

Leads an Agile ecommerce platform team supporting 11 brands across four technology stacks. Owns sprint planning, backlog prioritization, roadmap delivery, conversion optimization, merchandising, checkout, SEO, experimentation, and platform governance. Partners with engineering, UX, marketing, and content teams to translate business needs into product requirements. Tracks ecommerce performance metrics, drives A/B testing, standardizes experiences, and coordinates scalable platform improvements across brands.

Own client discovery, workflow mapping, AI solution design, implementation, testing, UAT, go-live, and post-launch value delivery for retail, e-commerce, hospitality, and restaurant clients. Translate operational needs into product specifications, coordinate engineering and solution teams, define success metrics, manage compliance requirements, travel to client sites, and influence the AI product roadmap through field insights.

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 roadmap, lifecycle, adoption, and reliability of Cyderes’ internal agentic AI harness. Build and evaluate agents and reusable skills, develop prototypes and production code, manage AI tools, and partner with Engineering, Security, UX, and product leadership. Define metrics, safety controls, cost and latency management, rollout plans, and portfolio decisions while improving workflows and operational outcomes.

Owns a SaaS product area from market discovery through roadmap delivery, adoption, retention, and revenue outcomes. The role requires AI-native product management, customer research, KPI ownership, rapid prototyping, cross-functional alignment, and product strategy. Responsibilities include mentoring Product Owners and Product Managers, improving Agile practices, translating customer needs into initiatives, and partnering with engineering, sales, marketing, customer success, and leadership.

Own Enterprise AI and IT product intake, roadmaps, prioritization, and cross-functional technology initiatives. Translate business needs into requirements, lead AI use cases from pilot to production, and hands-on test automations and agents for accuracy, safety, reliability, and adoption. Coordinate launches, change management, stakeholder communications, platform and vendor evaluations, integrations, and operational readiness across Engineering, IT, Security, Data, Legal, Operations, and business teams.

Lead strategy, roadmap, and execution for Intel’s data center AI software portfolio. Define enterprise-ready generative AI, agentic, microservices, and turnkey solutions across cloud, hybrid, and on-premises environments. Analyze competitors, develop go-to-market positioning, and grow relationships with cloud providers, ISVs, neoclouds, and open-source communities. Partner with engineering, AI research, silicon architecture, documentation, and developer relations teams to deliver PRDs, deployment blueprints, APIs, SDKs, and validated software offerings.

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.

Own the AI product roadmap, prioritization, accuracy metrics, model and vendor requirements, release planning, and correction feedback loop. Partner with engineering, product, tax, QA, UX, and client success to improve document extraction coverage, accuracy, cost, latency, and filing readiness across K1x products.

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.

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.

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.

Lead product definition and lifecycle for Arm's cloud AI compute subsystem offerings. Translate partner and market needs into engineering priorities, support partner enablement from RTL to physical implementation, and align cross-functional teams on roadmap and execution.

Leads strategy, roadmap, discovery, development, and launches for Stella, ServiceTrade’s agentic AI product suite. Partners with engineering, design, sales, marketing, and customer success to deliver trusted AI capabilities, manage backlogs and UAT, drive adoption, and align product execution with customer needs and business goals.

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.

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.