Sr AI Product Manager

United States·DallasRemoteFull Timesenior

EngineeringProduct ManagementData ScienceAi Product Manager

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Quick Summary

Technical Tools

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Bounteous is a premier end-to-end digital transformation consultancy dedicated to partnering with ambitious brands to create digital solutions for today’s complex challenges and tomorrow’s opportunities. With uncompromising standards for technical and domain expertise, we deliver innovative and strategic solutions in Strategy, Analytics, Digital Engineering, Cloud, Data & AI, Experience Design, and Marketing.

Our Co-Innovation methodology is a unique engagement model designed to align interests and accelerate value creation. Our clients worldwide benefit from the skills and expertise of over 4,000+ expert team members across the Americas, APAC, and EMEA. By partnering with leading technology providers, we craft transformative digital experiences that enhance customer engagement and drive business success.

We are seeking a Senior Product Manager, AI to build and scale AI-powered products in a complex enterprise environment.
This is a high-impact role for a hands-on builder and operator who thrives in ambiguity, moves quickly, and delivers outcomes, not just roadmaps.

You will take products from zero to one and drive them to meaningful adoption, operating like an internal startup founder at the intersection of product, engineering, and applied AI.

Role Focus
0→1 product development and rapid iteration
Scaling AI products to real adoption and business impact
Operating within complex enterprise systems and constraints
Bridging product, engineering, and applied AI

Promote and enforce awareness of key information security practices, including acceptable use of information assets, malware protection, and password security protocols

Identify, assess, and report security risks, focusing on how these risks impact the confidentiality, integrity, and availability of information assets

Understand and evaluate how data is stored, processed, or transmitted, ensuring compliance with data privacy and protection standards (GDPR, CCPA, etc.)

Ensure data protection measures are integrated throughout the information lifecycle to safeguard sensitive information

Product Strategy & Ownership

Define and execute a clear, outcome-driven vision for AI-powered capabilities (copilots, recommendations, summarization, search/chat, workflow automation)

Translate business goals into measurable product outcomes and prioritized roadmaps

Identify high-impact use cases through deep customer and stakeholder discovery

AI Product Development

Translate complex AI/ML capabilities into simple, intuitive, and trustworthy user experiences

Partner with engineering and data science to design and deliver solutions leveraging LLMs, RAG, and agentic architectures

Define AI system behavior, including inputs/outputs, confidence handling, fallback logic, and UX for uncertainty
Execution & Delivery

Drive end-to-end execution with strong ownership and urgency

Make high-quality product and technical tradeoffs (MVP vs scale, speed vs quality)

Manage cross-functional dependencies across engineering, design, data science, and business teams
AI Quality & Evaluation

Own evaluation frameworks (offline and online), including quality metrics, human review, and experimentation

Ensure systems meet standards for accuracy, latency, reliability, and user trust

Continuously improve performance through iteration and data-driven insights

Adoption & Change Management

Own adoption as a primary success metric, not just delivery

Design onboarding, enablement, and feedback loops that drive behavior change
Track and optimize engagement, usage, and business impact metrics

Stakeholder Leadership

Navigate complex enterprise environments with multiple stakeholders, legacy systems, and constraints
Influence without authority across product, engineering, sales, operations, and leadership teams
Communicate clearly with executives, translating technical concepts into business impact

Product & Execution

5–8+ years of product management experience in B2B or enterprise environments

Proven track record of building and scaling products from zero to one

Strong execution mindset with the ability to operate in ambiguity and deliver quickly

AI & Technical Depth

Hands-on experience shipping AI/ML or generative AI features in production

Strong working knowledge of LLMs, RAG systems, and agentic workflows

Experience defining evaluation frameworks, experimentation strategies, and AI performance metrics

Ability to collaborate deeply with engineering and data science on system design and tradeoffs

Adoption & Business Impact

Demonstrated success driving adoption in complex, change-resistant environments (e.g., sales, operations)

Strong analytical skills with the ability to connect product decisions to measurable business outcomes