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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.
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.
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.
Information Security Responsibilities
- 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
Core Responsibilities
- 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
Qualifications
- 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
- Deep product instincts, can distinguish high-impact solutions from low-value AI use cases
- Leadership & Communication
- Excellent communication and storytelling skills across technical and executive audiences
- High ownership mentality with a bias for action, resilience, and accountability
- Ability to influence and align cross-functional teams without formal authority
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Bounteous is proud to be an equal opportunity employer. Bounteous does not discriminate on the basis of race, religion, color, sex, gender identity, sexual orientation, age, physical or mental disability, national origin, veteran status, or any other status protected under federal, state, or local law. Bounteous is willing to sponsor eligible candidates for employment visas.
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What you need to know about the Austin Tech Scene
Austin has a diverse and thriving tech ecosystem thanks to home-grown companies like Dell and major campuses for IBM, AMD and Apple. The state’s flagship university, the University of Texas at Austin, is known for its engineering school, and the city is known for its annual South by Southwest tech and media conference. Austin’s tech scene spans many verticals, but it’s particularly known for hardware, including semiconductors, as well as AI, biotechnology and cloud computing. And its food and music scene, low taxes and favorable climate has made the city a destination for tech workers from across the country.
Key Facts About Austin Tech
- Number of Tech Workers: 180,500; 13.7% of overall workforce (2024 CompTIA survey)
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- Funding Landscape: $4.5 billion in VC funding in 2024 (Pitchbook)
- Notable Investors: Live Oak Ventures, Austin Ventures, Hinge Capital, Gigafund, KdT Ventures, Next Coast Ventures, Silverton Partners
- Research Centers and Universities: University of Texas, Southwestern University, Texas State University, Center for Complex Quantum Systems, Oden Institute for Computational Engineering and Sciences, Texas Advanced Computing Center

