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…