Technical AI Product Manager

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. They are seeking a Technical AI Product Manager who will define, build, and scale AI-powered products while collaborating with cross-functional teams to drive execution and align stakeholder interests.

Responsibilities:

• 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

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