Top Remote Technical Product Manager Jobs

Lead the definition and evolution of foundational platform capabilities, improving structural coherence across engineering organizations, and resolving cross-organizational problems.

Lead cross-portfolio product strategy and execution for Payment Integrity platform capabilities. Define multi-year roadmaps, prioritize initiatives, coordinate delivery across engineering and product teams, influence executive stakeholders, and mentor product leaders to deliver scalable, reusable platform solutions that improve payment accuracy, fraud detection, and operational efficiency.

Lead product definition, roadmap, and adoption for the CTOs agentic AI portfolio. Translate strategy into requirements, KPIs, and milestones; run discovery, prioritize backlogs, instrument usage, and shepherd incubation-to-handoff for AI/dev platforms and foundation-model tooling.

Own the AI and data product roadmap, prioritize and sequence development with engineering and founders, ship trustworthy AI experiences, drive adoption, define feature success metrics, evaluate outcomes, and manage the analytics foundation. The role requires technical fluency in AI, prior software engineering experience, production AI product delivery, strong product judgment, and comfort working in a fast-paced, remote startup environment.

Own end-to-end technical product requirements by engaging customers and stakeholders, running discovery, defining precise API/data specs and integrations, building lightweight internal tools or scripts, and validating solutions through acceptance and product health monitoring.

Own the advertising recommendation engine, including ranking quality, optimization objectives, guardrails, metrics, and model roadmap. Lead experiment design, inference standards, holdouts, rollback criteria, and production launches. Evaluate model performance and business impact with data science and stakeholders. Partner across ML, analytics, ad operations, pricing, identity, telemetry, and commercial teams. Apply advertising economics, ranking systems, SQL, and data-platform expertise to improve monetization for mobile apps and games.

Own the data and identity platform powering advertising, including event taxonomy, schemas, attribution, identity resolution, reporting APIs, real-time signals, and data contracts. Partner with engineering teams to build scalable interfaces for ads, machine learning, and customer reporting while ensuring compliance with GDPR, CCPA, ATT, SKAdNetwork, and consent requirements.

Lead product strategy and roadmap execution in a technical, spec-driven environment. Author detailed technical specifications, define APIs and data flows, write prototypes and lightweight automation, and contribute to code and deployments. Partner closely with engineering through design reviews, sprint planning, and pull request reviews. Establish product metrics, conduct experimentation and data analysis, research customers and competitors, and translate business and technical needs into shippable product increments.

Own the Agentforce Service Cloud adoption program from zero to 1,000 enterprise customers. Responsibilities include portfolio tracking, deployment velocity, blocker resolution, executive reporting, deployment playbook ownership, adoption metrics, customer feedback loops, and coordination across product, engineering, field, customer success, professional services, and partner teams. The role requires engineering depth, hands-on AI and agentic systems experience, Salesforce expertise, strong executive communication, and approximately 25% travel.

Own the vision, strategy, roadmaps, and deployment of AI and laboratory products supporting biologics discovery. Lead cross-functional teams of AI/ML researchers, engineers, and life scientists developing platforms for AI-guided target identification and drug design. Gather requirements, prioritize backlogs, define OKRs and KPIs, manage stakeholders, remove execution blockers, conduct user research, and drive product adoption across internal programs and external partnerships.

Own the vision, strategy, roadmap, and backlog for internal back-end platform products supporting engineering teams. Lead platform modernization initiatives, define platform capabilities and requirements, track KPIs, and partner with Platform Engineering, Enterprise Architecture, and application teams to deliver scalable, secure, reusable services, APIs, and developer tooling. Balance technical debt, operational needs, and long-term investments while guiding engineering stakeholders and ensuring reliability and quality standards.

Own technical capability roadmaps, prioritize program and ART backlogs, define feature requirements, and coordinate delivery across product teams, platforms, vendors, and technology organizations. Partner with architects, engineers, stakeholders, and risk teams to manage dependencies, risks, governance, release readiness, compliance, and production supportability. Track delivery progress, success metrics, adoption, and value realization while facilitating tradeoff decisions, stakeholder alignment, demonstrations, and continuous improvement.

Owns the C-BRAIN AI tool portfolio through product backlog management, milestone tracking, UAT coordination, vendor and contractor oversight, and technical program execution. Coordinates data engineering pipelines, infrastructure, data use agreements, compliance reviews, and external pharmaceutical, biotech, academic, and technology partners. Supports CTO working groups, technical reporting, consortium engagement, and stakeholder communications. Requires five years of progressive product or technical program management experience, external partner management, contract lifecycle expertise, and experience working with AI/ML or data engineering teams.

Lead the design and scaling of a unified fraud and risk platform. Define product roadmap, run data analysis and A/B tests, collaborate with engineers and data scientists to build real-time fraud detection, manage stakeholders, and balance customer experience with effective risk mitigation.

Lead design and scaling of a unified fraud and risk platform. Define product strategy, own fraud metrics, run SQL-driven analysis and A/B tests, and partner with engineers and data teams to build real-time detection, identity verification, and transaction monitoring. Balance customer experience with risk mitigation and communicate impact to executives, legal, and partners.

Own the technical roadmap for Company Operations, translating business needs into engineering specifications, prioritizing sprints, allocating capacity, and ensuring quality delivery. Partner with data engineering to evolve warehouse structures, establish business logic, validate data, and support financial and go-to-market reporting. Collaborate cross-functionally on build-versus-buy decisions, perform hands-on QA and data validation, and prototype with AI coding tools.

Own the end-to-end revenue cycle product roadmap, including eligibility, prior authorizations, claims-adjacent workflows, and EHR integrations. Translate clinic operations into product requirements, partner with Engineering on delivery and trade-offs, engage clinics and operations teams, define success metrics, and shape broader platform strategy. The role requires direct revenue cycle experience, strong communication, autonomy in a startup environment, and regular travel to NYC.

Owns the technical strategy, roadmap, requirements, and delivery of scalable data solutions. Partners with business, product, design, and engineering teams to prioritize high-impact features, assess vendors, guide architecture, incorporate AI strategies, and resolve technical issues. The role requires strong BI and data warehouse expertise, technical leadership, stakeholder communication, agile product development, customer delivery support, and mentoring responsibilities.

Own the technical product roadmap for a SaaS platform area, driving platform infrastructure, APIs, migrations, security, and scaling. Align Architecture and Engineering with Customer Success, Sales, and other teams; triage operational issues; monitor adoption and performance metrics; act as Product Owner when needed. Use AI tools daily to prototype, analyze data, draft technical specifications, and accelerate discovery while improving Product/Architecture handoffs.

Lead development and scaling of a payments orchestration platform: own routing, authorization, reconciliation, and settlement. Work hands-on with engineering and data (SQL) to optimize authorization, conversion, and costs; expand rails and integrations; coordinate with fraud, finance, ops, and BD; and communicate strategy to execs and partners.

Lead the design and scaling of a payments orchestration platform: own routing, reconciliation, settlement, metrics (authorization, conversion, cost, GMV), payment integrations, analytics, fraud coordination, and partner management while working hands-on with engineering, finance, and operations.

Lead development and scaling of a payments orchestration platform: own routing, authorization, settlement, reconciliation, and integrations across processors and rails. Drive payments strategy, run data analysis and SQL-backed experiments, collaborate with engineering, finance, fraud, and BD, and optimize authorization, conversion, and unit economics.

Lead product strategy and delivery for custom ad-sales applications. Manage full SDLC, create project and resource plans, run Scrum/stand-ups, write user stories, track progress, mitigate risks, and coordinate cross-functional teams to deliver scalable, revenue-driving solutions and post-production enhancements.

Lead consolidation and strategy for the company's AI platform: migrate distributed prompts to a unified system, prioritize chatbot work, drive architecture and API decisions, own the OpenAI relationship and ChatGPT App presence, evaluate emerging technologies (voicebot, computer capabilities), and coordinate engineering, data, and operations to deliver production-grade AI features.

Lead consolidation and technical strategy for Jerry.ai's AI platform. Own prompt migration, chatbot prioritization, vendor relationships (e.g., OpenAI/ChatGPT), and platform architecture. Coordinate engineering, data, and operations, drive execution, evaluate emerging voice/computer capabilities, and ensure the platform remains reliable while evolving to support scalable, production-grade AI agent products.