×
Register Here to Apply for Jobs or Post Jobs. X

VP, AI Product Manager - Data & AI

Job in New York City, Richmond County, New York, USA
Listing for: Ares Management
Full Time position
Listed on 2026-08-18
Job specializations:
  • Software Development
    AI Engineer (Applied/Software), DevOps, Software Architect
Job Description & How to Apply Below

VP Of Ai Platform Engineering

We are seeking an accomplished VP of AI Platform Engineering to lead the design, development, and deployment of our enterprise generative AI platform. This leadership role focuses on building and scaling core platform components that enable safe, secure, and compliant AI application development across the firm. Working closely with the Principal AI Platform Engineer and cross-functional teams, you will drive execution on critical platform infrastructure—from multi-LLM gateways and RAG services to model registry, prompt library, and production deployment pipelines.

This is an opportunity to shape how the organization leverages AI at scale while maintaining rigorous standards for security, governance, and reliability.

Key Responsibilities

Platform Development & Execution

  • Lead design and implementation of core platform components: multi-LLM gateway, RAG retrieval services, model registry, and prompt library
  • Drive execution on platform roadmap, breaking down complex features into deliverable milestones with clear success metrics
  • Own API design and service integration patterns that enable seamless consumption across AI enablement teams
  • Ensure technical excellence: code quality, testability, performance optimization, and architectural coherence

Multi-LLM Gateway & Model Management

  • Design and build multi-LLM gateway architecture supporting multiple providers (OpenAI, Anthropic, Azure, self-hosted, etc.)
  • Implement intelligent routing, load balancing, and fallback mechanisms based on cost, latency, and capability requirements
  • Build model registry with versioning, metadata management, and approval workflows
  • Implement cost optimization and Fin Ops tracking for model usage and spending
  • Monitor model performance, hallucination rates, latency, and quality metrics in production

RAG & Retrieval Infrastructure

  • Design and build enterprise RAG infrastructure: vector database integration, semantic search, and chunking strategies
  • Implement retrieval evaluation and quality metrics to ensure relevance and accuracy
  • Build indexing pipelines and data ingestion workflows from enterprise data sources
  • Integrate with data governance and lineage tracking systems

Model Context Protocol (MCP) & Integration Gateway

  • Implement MCP gateway for secure, standardized integration with external tools and APIs
  • Build tool catalog and discovery mechanisms for AI applications
  • Establish security and governance controls for tool access and data handling

Prompt Library & Version Control

  • Build organizational prompt library with versioning, tagging, and metadata
  • Implement testing and evaluation frameworks for prompt variants
  • Enable A/B testing and prompt performance analytics
  • Support prompt governance and approval workflows

Deployment Pipelines & Dev Ops

  • Design sandbox-to-production deployment pipelines with clear promotion gates and approval workflows
  • Implement CI/CD for AI applications: automated testing, integration, and deployment
  • Build monitoring, observability, and alerting for production AI systems
  • Implement canary deployments, gradual rollouts, and rollback mechanisms
  • Establish SLOs, error budgets, and on-call protocols for platform services

Agent-to-Agent (A2A) Workflows

  • Design orchestration framework for multi-step AI workflows with state management
  • Build error handling, retries, and recovery mechanisms for reliable execution
  • Implement workflow monitoring and debugging tools

Data Integration & Gateway Collaboration

  • Partner with Data Products team to design AI-native data access patterns and APIs
  • Implement secure, governed data retrieval for RAG and model training
  • Build metadata and data lineage tracking for compliance and governance

Security & Governance Implementation

  • Implement authentication, authorization, and encryption across platform services
  • Build audit logging, request validation, and rate limiting for all platform APIs
  • Implement input/output validation to prevent prompt injection and data leakage
  • Design model and prompt governance workflows with appropriate approval gates
  • Ensure compliance with firm security policies and regulatory requirements
  • Work with Compliance and Infosec teams on security assessments and incident response

Developer…

To View & Apply for jobs on this site that accept applications from your location or country, tap the button below to make a Search.
(If this job is in fact in your jurisdiction, then you may be using a Proxy or VPN to access this site, and to progress further, you should change your connectivity to another mobile device or PC).
 
 
 
Search for further Jobs Here:
(Try combinations for better Results! Or enter less keywords for broader Results)
Location
Increase/decrease your Search Radius (miles)
0
200
Filters
Education Level
Experience Level (years)
Posted in last:
Salary