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

Pay
$175,000–215,000/year · Base — pay source
Prior experience in investment banking or regulated financial services environments. Expected annualized base salary of $175,000 to $215,000. This range represents the low and high ends of the expected annualized base salary for this position. The specific base salary received by any employee will be informed by a number of factors, including but not limited to, role level and scope, location, candidate’s relevant qualifications, skills and experience.
Read the full posting
Work setting
Not stated
Employment
Full-time — employment source
Employment type in the employer’s posting: Full time
From the employer’s posting

What you’ll work on

Full posting
  • Build and operate the AI platform and developer tooling for Python AI apps

  • Build data pipelines with Azure Data Factory and Databricks for AI apps

  • Set up vector search and retrieval for RAG applications on Azure AI Search

  • Provision Azure infrastructure with Terraform or Bicep and run CI/CD pipelines

  • Implement data access controls, encryption and audit logging to SEC and FINRA rules

From the employer’s posting
Design, build, and operate the firm’s AI platform, enabling developers to build and deploy Python-based AI applications
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
Provision and maintain secure, scalable infrastructure on Azure (primary) and AWS using Infrastructure-as-Code (Terraform or Bicep)
Implement data access controls, encryption, and audit logging aligned with SEC and FINRA requirements

What you’ll bring

All qualifications

Core experience

  • Bachelor’s degree in computer science, Computer Engineering, or related field (Master’s degree is a plus);
  • 8+ years in infrastructure engineering, cloud platform engineering, or data engineering;
  • Demonstrated experience building shared platforms or developer services in an enterprise environment;
  • Strong Python skills: backend services, REST APIs (FastAPI or Flask), and automation scripting; PowerShell for infrastructure tasks;
  • Experience integrating LLM APIs (Anthropic Claude, Azure OpenAI) in production including token cost management and observability;
  • Familiarity with LLM application frameworks such as LangChain or Semantic Kernel;
Qualification wording
Bachelor’s degree in computer science, Computer Engineering, or related field (Master’s degree is a plus);
8+ years in infrastructure engineering, cloud platform engineering, or data engineering;
Demonstrated experience building shared platforms or developer services in an enterprise environment;
Strong Python skills: backend services, REST APIs (FastAPI or Flask), and automation scripting; PowerShell for infrastructure tasks;
Experience integrating LLM APIs (Anthropic Claude, Azure OpenAI) in production including token cost management and observability;
Familiarity with LLM application frameworks such as LangChain or Semantic Kernel;
Education & alternatives
PJT Partners seeks to hire individuals who are highly motivated, intelligent and have demonstrated excellence in prior endeavors. In addition, qualified candidates will possess the following: - Bachelor’s degree in computer science, Computer Engineering, or related field (Master’s degree is a plus); - 8+ years in infrastructure engineering, cloud platform engineering, or data engineering;
Apply at PJT Partners

Posting record

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Open 6 monthsWe first saw this posting 180 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.

Status in our records
Live
First seen by us
May 8, 2026180 days ago
Recorded sightings
124
Last seen by us
Nov 4, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

Pay

In line with similar jobs

$175K–$215K against $166K–$240K, the middle half of what similar US postings state.

From 1,279 postings in the last year. Stated ranges, not salaries paid.

Time since we first saw it

Day 180

Up longer than most. Similar jobs usually come down between day 6 and day 69.

From 4,347 similar postings that came down. Coming down is not always a hire.

PJT Partners is hiring

1 open job

  • Its jobs tend to stay up a long time
Hiring record

See how this role fits your experience

Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.

  • Python
  • SQL
  • AWS
  • Azure
  • Databricks
  • Docker
  • Kubernetes
  • S3
  • Terraform
  • FastAPI
  • Flask
Where the posting names them
Responsibilities The 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:
AI Platform & Developer Infrastructure - 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;
- Azure expertise: Azure AI Foundry, Azure Data Factory, Azure Databricks, AKS, Azure API Management, Azure Key Vault, Azure Entra ID; - Strong Python skills: backend services, REST APIs (FastAPI or Flask), and automation scripting; PowerShell for infrastructure tasks; - Infrastructure-as-Code: Terraform and/or Bicep; container orchestration with Docker and Kubernetes;
- 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. Cloud Infrastructure & DevOps
Cloud Infrastructure & DevOps - 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;
- DevSecOps practices: secrets management, SAST tooling, and secure CI/CD pipeline design; - Familiarity with AWS (Bedrock, S3, IAM) and agentic application frameworks (AutoGen, LangGraph); - Experience with Microsoft Fabric, Databricks Unity Catalog, or Azure Synapse;
- 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;
- 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.
Data Infrastructure & Pipelines - 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;
- 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;
- 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.
- Demonstrated experience building shared platforms or developer services in an enterprise environment; - Azure expertise: Azure AI Foundry, Azure Data Factory, Azure Databricks, AKS, Azure API Management, Azure Key Vault, Azure Entra ID; - Strong Python skills: backend services, REST APIs (FastAPI or Flask), and automation scripting; PowerShell for infrastructure tasks;
- Infrastructure-as-Code: Terraform and/or Bicep; container orchestration with Docker and Kubernetes; - Experience integrating LLM APIs (Anthropic Claude, Azure OpenAI) in production including token cost management and observability; - RAG pipeline experience: vector search (Azure AI Search or pgvector), document processing, and retrieval patterns;
- Experience integrating LLM APIs (Anthropic Claude, Azure OpenAI) in production including token cost management and observability; - RAG pipeline experience: vector search (Azure AI Search or pgvector), document processing, and retrieval patterns; - Familiarity with LLM application frameworks such as LangChain or Semantic Kernel;
- Familiarity with AWS (Bedrock, S3, IAM) and agentic application frameworks (AutoGen, LangGraph); - Experience with Microsoft Fabric, Databricks Unity Catalog, or Azure Synapse; - Azure certifications: AI-102, DP-203, or AZ-305;
- Experience with Microsoft Fabric, Databricks Unity Catalog, or Azure Synapse; - Azure certifications: AI-102, DP-203, or AZ-305; - Prior experience in investment banking or regulated financial services environments.
- 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.
- Strong Python skills: backend services, REST APIs (FastAPI or Flask), and automation scripting; PowerShell for infrastructure tasks; - Infrastructure-as-Code: Terraform and/or Bicep; container orchestration with Docker and Kubernetes; - Experience integrating LLM APIs (Anthropic Claude, Azure OpenAI) in production including token cost management and observability;

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About the role

We file this job under ML Engineer, by the work the posting describes.

ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.

Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.

A data scientist often works out which model to build; an ML engineer makes it run reliably in production.

US government figures for computer and information research scientists

Median yearly pay, May 2025
$140,300
Expected change, 2025 to 2035
21.8% more jobsagainst 3.5% for all jobs

The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.

Job description

View original posting ↗

PJT Partners is a global advisory-focused investment bank. Our team of senior professionals delivers a wide array of strategic advisory, shareholder advisory, restructuring and special situations and private fund advisory and placement services to corporations, financial sponsors, institutional investors and governments around the world. We offer a unique portfolio of advisory services designed to help our clients achieve their strategic objectives. We also provide, through PJT Park Hill, private fund advisory and fundraising services for alternative investment managers, including private equity funds, real estate funds and hedge funds.

From the beginning, PJT Partners has firmly believed that having the best people is key to building an enduring franchise. Our perspective was, and remains, that a great team brings in both top tier clients and appeals to a wide-range of diverse, talented colleagues. Fostering an inclusive culture, which welcomes differing perspectives and beliefs, enables us to provide the best advice and insights to our clients.

To learn more about PJT Partners, please visit our website at www.pjtpartners.com. 

Responsibilities

The 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:

AI Platform & Developer Infrastructure

  • 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.

Data Infrastructure & Pipelines

  • 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.

Cloud Infrastructure & DevOps

  • 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.

Security, Governance & Compliance

  • 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.

Collaboration & Documentation

  • 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.

Qualifications

PJT Partners seeks to hire individuals who are highly motivated, intelligent and have demonstrated excellence in prior endeavors. In addition, qualified candidates will possess the following:

  • Bachelor’s degree in computer science, Computer Engineering, or related field (Master’s degree is a plus);
  • 8+ years in infrastructure engineering, cloud platform engineering, or data engineering;
  • Demonstrated experience building shared platforms or developer services in an enterprise environment;
  • Azure expertise: Azure AI Foundry, Azure Data Factory, Azure Databricks, AKS, Azure API Management, Azure Key Vault, Azure Entra ID;
  • Strong Python skills: backend services, REST APIs (FastAPI or Flask), and automation scripting; PowerShell for infrastructure tasks;
  • Infrastructure-as-Code: Terraform and/or Bicep; container orchestration with Docker and Kubernetes;
  • Experience integrating LLM APIs (Anthropic Claude, Azure OpenAI) in production including token cost management and observability;
  • RAG pipeline experience: vector search (Azure AI Search or pgvector), document processing, and retrieval patterns;
  • Familiarity with LLM application frameworks such as LangChain or Semantic Kernel;
  • Cloud security fundamentals: RBAC, managed identities, private endpoints, Key Vault, and network segmentation;
  • DevSecOps practices: secrets management, SAST tooling, and secure CI/CD pipeline design;
  • Familiarity with AWS (Bedrock, S3, IAM) and agentic application frameworks (AutoGen, LangGraph);
  • Experience with Microsoft Fabric, Databricks Unity Catalog, or Azure Synapse;
  • Azure certifications: AI-102, DP-203, or AZ-305;
  • Prior experience in investment banking or regulated financial services environments.

Expected annualized base salary of $175,000 to $215,000.

This range represents the low and high ends of the expected annualized base salary for this position. The specific base salary received by any employee will be informed by a number of factors, including but not limited to, role level and scope, location, candidate’s relevant qualifications, skills and experience.

Base salary is one component of PJT Partners’ compensation structure. In addition to base salary, PJT Partners’ compensation structure may include additional rewards, incentives and benefits, including but not limited to, a discretionary bonus component.

PJT is an equal opportunity employer. We do not discriminate on the basis of, and will consider all qualified applicants for employment without regard to race, color, religious creed, religion, sex, pregnancy, national origin, ancestry, citizenship status, age, marital or partnership status, sexual orientation, gender identity expression, disability, medical condition, genetic information or predisposition, veteran or military status, status as a victim of domestic violence, a sex offense or stalking, or any other category protected by law. PJT Partners also complies with all applicable laws with regard to providing reasonable accommodation of disabilities to applicants. For more information or to request an accommodation, please contact Human Resources.

California Applicants: PJT Partners will consider for employment qualified applicants with arrest and/or conviction records in a manner consistent with applicable law including, but not limited to, the San Francisco Fair Chance Ordinance and/or Los Angeles Fair Chance Initiative for Hiring Ordinance.

Applicant Privacy Notice:

View our Applicant Privacy Notice https://info.pjtpartners.com/PJT_Global_Applicant_Privacy_Notice here. If you are a California resident, please refer to our California Applicant Privacy Notice https://info.pjtpartners.com/California_Applicant_Privacy_Notice for further information.


*In order to be considered, please ensure your resume/CV is submitted in PDF format.

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Pay
Prior experience in investment banking or regulated financial services environments. Expected annualized base salary of $175,000 to $215,000. This range represents the low and high ends of the expected annualized base salary for this position. The specific base salary received by any employee will be informed by a number of factors, including but not limited to, role level and scope, location, candidate’s relevant qualifications, skills and experience.
Location & working pattern

New York

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