Bounteous - Technical AI Product Manager
Requirements
• 10+ years of Product Management experience, including experience working on AI products. • Strong technical understanding of systems design and thinking, data, platforms and modern software architectures. • Strong experience driving product launch strategy, GTM planning, and user adoption initiatives • Experience working with AI/ML systems, including concepts such as: • LLMs and Generative AI • Retrieval-Augmented Generation (RAG) • Vector Databases • Model serving and inference architectures • AI safety, governance, and guardrails • Data integration and orchestration pipelines • Ability to communicate effectively with both technical and non-technical stakeholders including Sr/Directors and VPs. • Strong analytical, problem-solving, and prioritization skills. • Experience with rapid AI prototyping, vibe coding workflows, and building evaluation or testing harnesses for LLM-based applications • Familiarity with GCP/AWS/cloud-native architectures and MLOps practices. • Experience working with experimentation frameworks, evaluation pipelines, or AI observability tooling. • Background working in highly cross-functional product and engineering environments. • Success Criteria • Outcome/KPI-driven product management mindset with experience driving feature prioritization, adoption, and measurable business impact. • Strong product rigor with the ability to drive adoption and ROI through deep user understanding, cohort analysis, customer research, and industry/best-practice insights. • Excellent storytelling, communication, and narrative-building skills with the ability to articulate product vision, influence stakeholders, and galvanize cross-functional teams. • Strong orchestration and accountability management capabilities across client stakeholders, product, engineering, and business teams to drive alignment and execution. • $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 • Define product vision, roadmap, and execution strategy for AI-driven products and platforms. • Partner with engineering, AI, data, and infrastructure teams to deliver scalable AI solutions. • Drive product discovery, requirements definition, prioritization, and go-to-market planning. • Collaborate on capabilities including model serving, orchestration, data pipelines, and evaluation. • Collaborate to define scalable architectures for AI apps~ RAG, Data integrations, and AI guardrails. • Translate customer and business needs into features and measurable outcomes. • Monitor product performance, adoption, reliability, and operational metrics. • Drive stakeholder alignment across business, engineering, security, compliance, and operations.
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