Generative AI Platform Manager, Vice President

About the Role We're seeking a strategic, hands-on VP to lead the design and delivery of our enterprise Generative AI platform. Primary depth required in AWS Bedrock, Azure AI Foundry, Azure OpenAI, and Databricks , with strong skills in IaC authorship, Harness CI/CD, FinOps, and AI-assisted developer tooling. You'll set technical direction, author production-grade constructs, mentor senior engineers, and enable data scientists and application teams to ship Gen AI solutions at scale. Key Responsibilities AWS Bedrock Platform (Primary) Own enterprise Bedrock strategy: model access governance, provisioned throughput, cross-region inference, multi-account architecture Operationalize Knowledge Bases, Agents, Guardrails, Prompt Management, Flows, and Model Evaluation Lead FM lifecycle across Claude, Nova/Titan, Llama, Mistral, and Cohere Design RAG on Bedrock with OpenSearch Serverless, Aurora pgvector, and Kendra Optimize consumption: on-demand vs. PT, model routing, prompt caching, token efficiency Azure AI Foundry & Azure OpenAI (Primary) Own Foundry hub/project architecture, model catalog governance, and quota management Lead Azure OpenAI patterns (PTU vs. PAYG, capacity planning, content filters) across GPT-4o, GPT-4.1, and o-series models Architect RAG/agent workloads with AI Search, prompt flow, and Agent Service Implement Content Safety, private networking, Entra ID, CMK, and data residency controls Databricks & Data-Centric AI (Primary) Own Databricks strategy on AWS and Azure: workspace architecture, Unity Catalog, cluster policies Lead Mosaic AI adoption: Model Serving, Vector Search, Feature Store, AI Gateway, MLflow Architect fine-tuning/pretraining pipelines and lakehouse-native RAG on Delta Lake Establish DBU cost controls and serverless governance Infrastructure as Code & Golden Paths Author L2/L3 CDK constructs (TypeScript/Python), Bicep modules, and Terraform for multi-cloud AI infra Codify secure-by-default "golden paths" enabling teams to launch Gen AI workloads in hours Standardize config-as-code, secrets management, and drift detection Harness CI/CD Own Harness pipelines, templates, and delegates for Bedrock, Azure OpenAI, Foundry, and Databricks Asset Bundles Integrate with GitOps, Terraform/CDK/Bicep, OPA policy-as-code, and approval gates Establish reference pipelines with linting, security scanning, model eval, and cost checks Developer Experience Champion Claude Desktop, MCP servers, and AI coding assistants (Copilot, Cursor, Claude Code) Build internal MCP servers exposing enterprise systems to agentic clients Define secure usage patterns for regulated environments; measure productivity impact Governance & Leadership Establish security, compliance, and responsible AI controls (red-teaming, audit logging, guardrails) Build observability across CloudWatch, Azure Monitor, Databricks system tables, Grafana, Datadog Partner with Data, MLOps, Security, and Application leadership; recruit and mentor a top-tier team Required Skills Bedrock: Knowledge Bases, Agents, Guardrails, Flows, PT; Claude, Nova, Llama, Mistral; RAG and vector stores (OpenSearch, pgvector, Pinecone, Kendra); agent frameworks (Bedrock Agents, LangGraph, Strands) Azure AI: Foundry hubs/projects, prompt flow, Agent Service; Azure OpenAI (GPT-4o/4.1, o-series, PTU); AI Search; Content Safety Databricks: Mosaic AI, Vector Search, AI Gateway, MLflow, Unity Catalog, Asset Bundles, Delta Lake IaC: CDK L2/L3 (TS/Python), Bicep, Terraform (multi-cloud), secrets management CI/CD: Harness (YAML pipelines, delegates, templates, GitOps), OPA/Rego, GitHub Actions, Azure DevOps FinOps: Token/PTU/DBU governance, tagging, chargeback, capacity planning, token/model optimization Dev Tooling: Claude Desktop, MCP server authoring, Claude Code, Copilot, Cursor Cloud: Deep AWS + Azure (networking, IAM/Entra ID, private endpoints); Docker/Kubernetes (EKS/AKS); serverless; API design; complementary GCP/Vertex AI Data: Delta Lake, Unity Catalog, RAG/fine-tuning data pipelines, governance/lineage Observability: CloudWatch, Azure Monitor, App Insights, Grafana, Arize, Datadog Languages: Python (primary), TypeScript Leadership: Scaling senior teams hands-on, executive communication, owning budgets/roadmaps Education & Experience Bachelor's or Master's in CS, Engineering, or IT 10+ years in platform/cloud/SRE engineering 5+ years hands-on AWS and Azure with production depth in Bedrock, Azure OpenAI/Foundry, and Databricks 3+ years in technical leadership or people management Financial services or regulated-industry experience strongly preferred Preferred Qualifications Published CDK construct libraries, Bicep registries, or Terraform modules consumed enterprise-wide Enterprise-scale Harness pipeline authoring and rollout Fine-tuning/continued pretraining experience (LoRA, QLoRA, RLHF, DPO) on Mosaic AI, Azure OpenAI, or Bedrock Custom Models Model optimization: quantization, distillation, prompt caching, speculative decoding PTU/PT capacity planning at scale Production MCP servers and Claude Desktop deployments in regulated environments Agentic frameworks (Bedrock Agents, Azure AI Agent Service, Databricks Agent Framework, LangGraph, Strands) AI safety/guardrail frameworks (Bedrock Guardrails, Azure Content Safety, NeMo, Guardrails AI) Measurable FinOps wins (token/DBU/inference cost reduction) Open-source contributions (CDK, Terraform providers, MCP) Multi-tenant AI platforms with chargeback/showback Board/regulator-level presentation experience Certifications (one or more preferred) AWS: Solutions Architect Pro, ML Specialty, DevOps Engineer Pro Azure: AZ-305, AI-102, AZ-400, OP-100 Databricks: Data Engineer Pro, ML Pro, or Generative AI Engineer Associate GCP: Professional Cloud Architect or ML Engineer (complementary) Harness: Certified Expert (CD or Platform) Anthropic: Claude Builder or pa