Senior Product Owner- Tech Ex AI Assets Foundry Team

West Monroe•Washington, DC

4d•$184,900 - $250,100•Remote

About The Position

The Tech Ex Labs Senior Product Owner will define and deliver the roadmap for the firm's portfolio of proprietary software assets and AI capabilities. This role partners with business leaders, AI architects, engineers, product design, governance, and product success teams to turn market and client needs into scalable, secure, responsible AI-enabled products. The ideal candidate brings senior product ownership experience and practical depth in generative AI, agentic AI, machine learning, data platforms, cloud services, and AI governance.

Requirements

Bachelor's degree in Business, Computer Science, Engineering, Information Systems, Data Science, or a related field preferred; equivalent experience accepted.
7+ years of experience in product management, product ownership, technology delivery, platform management, AI/ML programs, or related disciplines.
2+ years of experience supporting AI, machine learning, analytics, data platforms, cloud-based products, generative AI, agentic AI, or AI-enabled software capabilities.
Strong understanding of Agile/Scrum delivery and experience leading cross-functional Agile teams.
Proven track record delivering customer-centric technology products aligned to business objectives, adoption goals, and measurable outcomes.
Experience collaborating with engineering, architecture, data, AI/ML, design, governance, business, and executive stakeholders.
Ability to travel as needed for team meetings, workshops, stakeholder sessions, or conferences.
Practical understanding of the AI/ML lifecycle, including data ingestion, model development, evaluation, deployment, monitoring, retraining, and continuous improvement.
Familiarity with generative AI, agentic AI concepts, AI platform architecture, MLOps, cloud-native technologies, and enterprise technology ecosystems.
Working knowledge of data engineering, platform engineering, AI governance, security, compliance, privacy, and responsible AI frameworks.
Strong product strategy, roadmap development, backlog prioritization, release planning, and metrics-driven decision-making skills.
Ability to translate ambiguous business needs into product requirements, technical capabilities, user stories, acceptance criteria, and success metrics.
Strong analytical and problem-solving skills, with the ability to use customer feedback, performance metrics, and adoption data to guide product decisions.
Ability to balance competing stakeholder priorities while maintaining focus on business value, feasibility, risk, and delivery outcomes.
Excellent stakeholder management, executive communication, facilitation, and organizational skills.
Ability to lead cross-functional decision-making across business, product, design, engineering, data, AI/ML, and governance teams.
Ability to communicate a compelling product vision and adapt quickly to evolving AI technologies, market trends, and business needs.

Responsibilities

Define and maintain the vision, strategy, roadmap, and outcome measures for proprietary software assets and AI capabilities.
Use market trends, client feedback, emerging AI capabilities, competitive signals, and product performance to inform priorities.
Own the AI product backlog, including feature prioritization, release planning, feature decomposition, user stories, and acceptance criteria.
Translate business problems and user needs into clear requirements for engineering, data, AI/ML, and asset delivery teams.
Make tradeoff decisions that balance speed, value, quality, technical debt, security, compliance, and responsible AI considerations.
Lead sprint planning, backlog refinement, reviews, and delivery ceremonies to ensure increments meet roadmap goals and KPIs.
Partner with product design, engineering, AI/ML, data, and platform teams to shape solution approaches for initiatives, epics, and stories.
Manage delivery, model, data, privacy, security, operational, and adoption risks; support UAT, defect resolution, release readiness, and post-launch measurement.
Serve as the product liaison across business stakeholders, AI architects, data team, ML engineers, asset engineers, product designers, governance, and product success teams.
Gather, evaluate, and prioritize requirements from internal users, client-facing teams, asset teams, and AI development teams.
Drive adoption through enablement, training, best practices, change management, feedback loops, and clear executive communication.
Embed responsible AI requirements into product features and release criteria, including transparency, auditability, monitoring, data quality, human oversight, and risk controls.
Evaluate emerging AI, MLOps, data, cloud, and automation technologies that could strengthen the firm's proprietary software asset portfolio.
Identify opportunities to improve developer productivity, reduce operational cost, increase reliability, and standardize repeatable patterns across AI and software assets.
Champion a product mindset focused on customer experience, measurable business outcomes, reusable capabilities, continuous delivery, and scalable operations.