Generative AI Platform Manager, Vice President

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.

- 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

- 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

- 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

- 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

- 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

- 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

- 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

- 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

- 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

- 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

- 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 partner credentials