Vice President - Technology (Senior Data & AI Infrastructure Platform Engineer)

Data And Ai Infrastructure EngineerThe PJT Partners Technology team is responsible for creating and continuously improving a robust and secure technology foundation that supports the firm's business activities. Our Technology team is seeking a Data and AI Infrastructure Engineer to build secure, scalable platforms and pipelines that power the firm's AI initiatives. This is a platform engineering role — the focus is building the infrastructure and developer tooling that enables teams to rapidly develop and deploy AI-powered Python applications using Azure AI Foundry and the Claude API (Anthropic), not training custom models.

You will work with data engineers, application developers, architects, and business stakeholders to deliver AI-ready infrastructure that meets the firm's security and compliance requirements.Responsibilities include:Design, build, and operate the firm's AI platform, enabling developers to build and deploy Python-based AI applications;Implement and manage Azure AI Foundry environments: model deployments, AI hubs, project workspaces, and access controls;Integrate and operationalize third-party AI APIs (Anthropic Claude API, Azure OpenAI) with secure access patterns, API gateway controls, rate limiting, and cost monitoring;Build internal developer tooling and SDK scaffolding to accelerate AI application development across the firm.Build and maintain data pipelines using Azure Data Factory and Azure Databricks to serve AI application data needs;Implement vector search and document retrieval infrastructure (Azure AI Search) to support RAG-based applications;Manage structured and unstructured data stores including Azure Data Lake, Azure SQL, and Cosmos DB.Provision and maintain secure, scalable infrastructure on Azure (primary) and AWS using Infrastructure-as-Code (Terraform or Bicep);Build and maintain CI/CD pipelines for AI application deployment via Azure DevOps or GitHub Actions;Manage containerized workloads using Docker and Kubernetes (AKS) for AI application hosting and API services;Drive Secure DevOps practices including secrets management, dependency scanning, and policy enforcement.Implement data access controls, encryption, and audit logging aligned with SEC and FINRA requirements;Design MNPI data segregation controls and enforce AI governance guardrails including content filtering and usage logging for all AI API integrations;Manage identity and access for AI platforms using Azure Entra ID, RBAC, and managed identities;Collaborate with Compliance and Legal to ensure AI usage policies are enforced at the infrastructure level.Produce architecture designs, runbooks, and technical documentation for all platform components;Support application developers building AI-powered applications with platform guidance and troubleshooting;Partner with solution architects, data engineers, and business stakeholders to translate requirements into infrastructure.