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