S

State Street

Holds assets for institutions and runs index funds

Generative AI Platform Manager

Engineering LeadershipConfirmed live in the last 24 hours
Full-timeIn-person

About the Job

Requirements

  • Demonstrated expertise with AWS Bedrock, including Knowledge Bases, Agents, Guardrails, Flows, provisioned throughput, Claude, Nova, Llama, Mistral, retrieval-augmented generation (RAG), vector stores, and agent frameworks.
  • Demonstrated expertise with Azure AI Foundry, Azure OpenAI, prompt flow, Agent Service, AI Search, and Content Safety.
  • Demonstrated expertise with Databricks Mosaic AI, Vector Search, AI Gateway, MLflow, Unity Catalog, Asset Bundles, and Delta Lake.
  • Experience authoring CDK L2/L3 constructs in TypeScript or Python, Bicep modules, Terraform, and secrets management.
  • Experience with Harness YAML pipelines, delegates, templates, GitOps, Open Policy Agent (OPA)/Rego, GitHub Actions, and Azure DevOps.
  • Expertise in FinOps governance for tokens, provisioned throughput units (PTUs), Databricks Units (DBUs), tagging, chargeback, capacity planning, and token/model optimization.
  • Experience with Claude Desktop, Model Context Protocol (MCP) server authoring, Claude Code, Copilot, and Cursor.
  • Deep AWS and Azure experience including networking, identity and access management (IAM)/Entra ID, and private endpoints; Docker/Kubernetes (EKS/AKS), serverless, and API design.
  • Experience with Delta Lake, Unity Catalog, RAG/fine-tuning data pipelines, data governance, and lineage.
  • Experience with CloudWatch, Azure Monitor, Application Insights, Grafana, Arize, and Datadog.
  • Python and TypeScript skills, with Python as the primary language.
  • Ability to scale senior teams hands-on, communicate with executives, and own budgets and roadmaps.
  • A bachelor's or master's degree in Computer Science, Engineering, or Information Technology.
  • At least 10 years of platform, cloud, or site reliability engineering experience.
  • At least 5 years of hands-on AWS and Azure experience, with production depth in Bedrock, Azure OpenAI/Foundry, and Databricks.
  • At least 3 years of technical leadership or people-management experience.

Responsibilities

  • Own enterprise Bedrock strategy, including model-access governance, provisioned throughput, cross-region inference, and multi-account architecture.
  • Operationalize Knowledge Bases, Agents, Guardrails, Prompt Management, Flows, and Model Evaluation.
  • Lead the foundation-model lifecycle across Claude, Nova/Titan, Llama, Mistral, and Cohere.
  • Design RAG on Bedrock using OpenSearch Serverless, Aurora pgvector, and Kendra.
  • Optimize consumption through on-demand versus provisioned throughput, model routing, prompt caching, and token efficiency.
  • Own Foundry hub/project architecture, model-catalog governance, and quota management.
  • Lead Azure OpenAI patterns across GPT-4o, GPT-4.1, and o-series models, including PTU versus pay-as-you-go, capacity planning, and content filters.
  • Architect RAG and agent workloads using AI Search, prompt flow, and Agent Service.
  • Implement Content Safety, private networking, Entra ID, customer-managed keys, and data-residency controls.
  • Own Databricks strategy on AWS and Azure, including workspace architecture, Unity Catalog, and cluster policies.
  • Lead Mosaic AI adoption across Model Serving, Vector Search, Feature Store, AI Gateway, and 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, Bicep modules, and Terraform for multi-cloud AI infrastructure.
  • Codify secure-by-default golden paths so teams can launch generative AI workloads in hours.
  • Standardize configuration-as-code, secrets management, and drift detection.
  • Own Harness pipelines, templates, and delegates for Bedrock, Azure OpenAI, Foundry, and Databricks Asset Bundles.
  • Integrate Harness with GitOps, Terraform/CDK/Bicep, OPA policy-as-code, and approval gates.
  • Establish reference pipelines with linting, security scanning, model evaluation, and cost checks.
  • Promote Claude Desktop, MCP servers, and AI coding assistants such as Copilot, Cursor, and Claude Code.
  • Build internal MCP servers that expose enterprise systems to agentic clients.
  • Define secure usage patterns for regulated environments and measure productivity impact.
  • Establish security, compliance, and responsible-AI controls, including red-teaming, audit logging, and guardrails.
  • Build observability across CloudWatch, Azure Monitor, Databricks system tables, Grafana, and Datadog.
  • Partner with Data, MLOps, Security, and Application leadership, and recruit and mentor a team.

Desired Qualifications

  • Financial-services or regulated-industry experience.
  • Published CDK construct libraries, Bicep registries, or Terraform modules consumed enterprise-wide.
  • Enterprise-scale Harness pipeline authoring and rollout experience.
  • Fine-tuning/continued pretraining experience using LoRA, QLoRA, RLHF, or DPO on Mosaic AI, Azure OpenAI, or Bedrock Custom Models.
  • Model-optimization experience with quantization, distillation, prompt caching, or speculative decoding.
  • PTU/PT capacity-planning experience at scale.
  • Production MCP servers and Claude Desktop deployments in regulated environments.
  • Experience with agentic frameworks including Bedrock Agents, Azure AI Agent Service, Databricks Agent Framework, LangGraph, or Strands.
  • Experience with AI safety/guardrail frameworks including Bedrock Guardrails, Azure Content Safety, NeMo, or Guardrails AI.
  • Demonstrated FinOps results reducing token, DBU, or inference costs.
  • Open-source contributions to CDK, Terraform providers, or MCP.
  • Experience with multi-tenant AI platforms and chargeback/showback.
  • Board- or regulator-level presentation experience.
  • One or more preferred certifications: AWS Solutions Architect Professional, ML Specialty, or DevOps Engineer Professional; Azure AZ-305, AI-102, AZ-400, or OP-100; Databricks Data Engineer Professional, ML Professional, or Generative AI Engineer Associate; GCP Professional Cloud Architect or ML Engineer; Harness Certified Expert (CD or Platform); or Anthropic Claude Builder or partner credentials.

About the Company

State Street

Holds assets for institutions and runs index funds

State Street holds and services investments for pension funds, insurers, fund companies, and other large institutions, and it also runs index funds through State Street Investment Management. It launched the first US-listed exchange-traded fund, the SPDR S&P 500 ETF Trust, in 1993, and in 1924 it became custodian of the first US mutual fund. As a custody bank, it safekeeps clients' stocks and bonds, completes their trades, calculates what their funds are worth, and lends their securities to other investors. It earns fees on the assets it services and manages, plus income from currency trading and from interest on client cash. State Street traces its roots to a bank chartered in 1792 and is based in Boston, Massachusetts.

Company size
10,001+
Company stage
IPO
Headquarters
Boston, MA
Founded
1792

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