Bounteous - Sr AI Product Manager
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Requirements
• 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 • $130,000 - $140,000 a year • We invite you to stay connected with us by subscribing to our monthly job openings alert here.
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 • 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
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