Hiring: VP, AI Product Manager - Data & AI Company: Ares Management Location: New York, NY Job Posted Time: 2026-09-03 14:30:01 Target Skills & Keywords : Change Management, Databricks, LLM, Product Management, Program Management, RAG About the job Experience: •8+ years in product management; 3+ years in an AI, ML, or data product role with direct ownership of LLM or generative AI use cases from discovery through production •Demonstrated experience translating complex, knowledge-intensive workflows (legal review, research, financial analysis, report generation) into AI product requirements that engineering teams can execute against •Track record of managing multi-stakeholder use-case portfolios with competing priorities across business functions — not just a single product line •In-depth knowledge of RAG architectures, agentic workflows, prompt design tradeoffs, and retrieval quality concepts — sufficient to write precise requirements and hold technical conversations with AI Engineering •Exceptional written communication: able to produce crisp product specs, executive memos, board-ready summaries, and governance submission packages with equal fluency Required Skills: •The VP, AI Product Manager is a senior product leader within the central hub, responsible for defining what the firm builds with AI and why — translating the needs of investment professionals, operations teams, IR, legal, and compliance into a coherent AI use-case portfolio that delivers measurable business value. •This is a strategic and execution-oriented role in equal measure. You will partner with vertical PM tech teams and run discovery with deal teams, IR, and operations; write crisp product specs that engineering can execute against; define success metrics; and manage the use-case funnel across investment and corporate functions. •Own the enterprise AI use-case roadmap across all firm functions — deal execution, portfolio operations, investor relations, legal & compliance, and firm-wide productivity — with prioritization aligned to business leadership •Define and maintain the AI use-case intake funnel: structured discovery, feasibility scoring, value estimation, and sequencing logic that balances strategic impact with engineering capacity •Translate high-level business goals (analyst time savings, decision support, operational efficiency) into a portfolio of AI initiatives with clear owners, milestones, and success criteria •Stay current on generative AI and agentic capabilities; proactively identify where emerging platform primitives (MCP integrations, A2A workflows, new model capabilities) unlock net-new use cases for the firm •Lead structured discovery sessions with deal teams, portfolio operations, IR, legal, compliance, and senior stakeholders to surface high-value AI opportunities and translate them into product requirements •Produce well-structured product specifications: user stories, workflow diagrams, acceptance criteria, context layer definitions (Firm/Deal/User), retrieval scope, and output format requirements — written to the standard AI Engineering executes against Qualifications: •Private equity, investment banking, asset management experience — familiarity with deal workflows, IC memo process, fund reporting cycles, LP communications, or portfolio monitoring •Operational familiarity with Databricks, Unity Catalog, or enterprise data platforms — sufficient to understand how data product maturity constrains AI use-case delivery •Prior experience in a hub-and-spoke or federated operating model — comfortable defining central platform policy while enabling vertical teams to move with autonomy •MBA or advanced degree in a relevant field (finance, computer science, information systems) is a plus but not required Compensation: •$225,000 - $275,000 / year •Total compensation may also include a discretionary performance-based bonus Interested candidates, please apply directly through the job posting on company's career page or try via AI auto apply on this platform. Don't miss this opportunity to join a forward-thinking team!