Summer 2027 Graduate Intern – Super Intelligence (SI) Connectors Platform Engineer (MCP and RAG) – IT

Federal Reserve Board; Washington (District of Columbia); Hybrid; USD 37.000 - 39.000; Vollzeit

Zusammenfassung

Federal Reserve Board invites motivated students for a SI/AI Platform internship in the AIS unit. You will work on building, deploying, and securing MCP servers to connect enterprise data with SI/AI tools, using Python, PostgreSQL with pgvector, and cloud-native technologies.

You will collaborate with data scientists, economists and engineers, gain hands-on experience in Kubernetes, Terraform, Ansible, and GitLab CI, and contribute to platform security and governance in a regulated environment.

Qualifikationen

• Programming in Python preferred.
• Knowledge of large language model tooling and concepts.
• Familiarity with infrastructure as code and CI/CD practices.

Aufgaben

• Build and deploy MCP servers exposing Board data sources to SI/AI clients.
• Test and deploy RAG components and vector search on PostgreSQL.
• Contribute to Terraform, Ansible, GitLab CI pipelines and ArgoCD deployments.

Kenntnisse

Python

Large language model tooling

Infrastructure as code

CI/CD pipelines

Linux

REST APIs

Documentation

Ausbildung

Undergraduate or graduate student in CS/Engineering

Tools

Kubernetes

AWS

Terraform

Ansible

GitLab CI

pgvector

Jobbeschreibung

Minimum Education

Enrolled in an undergraduate or graduate degree program at an accredited university and returning to continue studies after the internship.

Minimum Experience

0

Summary

The Federal Reserve Board (Board) provides students opportunities for career success. The Board’s Internship program is designed to provide valuable work experience for undergraduate and graduate students considering careers including, but not limited to, economics, finance and accounting, information systems, and data analysis. The Board believes that by combining academic endeavors with project‑related work experience, qualified and capable college students can gain the practical knowledge need in a competitive global job market. Internships are paid positions with salaries commensurate with credit hours; internships may be in‑person, remote or hybrid, depending on the needs of the team. Employment in the Board’s internship program is granted to U.S. citizens. Applicants must be currently enrolled in an undergraduate or graduate degree program at an accredited university and returning to continue studies after the internship. Interns receive a syllabus or research project plan outlining their projects and goals for the internship. Interns are assigned a supervisor or mentor to guide them through their internship, and regular check‑in meetings with their manager to manage performance expectations and assist with learning goals. Interns have access to a wide range of training programs and events for professional development purposes.

As a Super Intelligence (SI/AI) Connectors Platform intern, you will work in the Application Infrastructure Support (AIS) unit of the Division of Information Technology, on the team building the Board's governed platform for connecting SI/AI tools to enterprise data and systems. The team designs, hosts, and operates Model Context Protocol (MCP) servers, retrieval‑augmented generation (RAG) services, and the identity, gateway, and inventory layer that lets SI/AI applications and agents reach Board data securely. The platform runs on Kubernetes (Amazon EKS) in the Board's AWS environment and is built and delivered entirely through infrastructure as code and CI/CD pipelines. You will work alongside the Board's SI/AI Program and with the data scientists, economists, and analysts who use these connectors.

What You'll Be Doing

SI/AI Connectors Platform interns support the team in

• Building and deploying MCP servers that expose Board data sources and tools to SI/AI clients such as Claude Code and Claude Desktop, using Python and the MCP SDK
• Standing up and testing RAG components: document ingestion, chunking, embeddings, and vector search on PostgreSQL with pgvector
• Delivering platform changes the way the team does: Terraform for cloud infrastructure, Ansible for configuration, GitLab CI pipelines for build and test, and ArgoCD GitOps for deployment to Kubernetes
• Contributing to the identity and access layer for SI/AI connectors, including OAuth client registration, audience‑bound tokens, and routing through the LiteLLM gateway
• Populating and maintaining the MCP connector inventory and catalog so Board staff can discover what connectors exist, who owns them, and how to connect
• Writing the templates, documentation, and quick‑start guides that let other Board teams build connectors to enterprise standards
• Participating in daily stand‑ups, sprint planning, and design reviews with engineers, architects, and the SI/AI Program

Learning Objectives

Over The Course Of The Internship, The Intern Will

• Build, containerize, and deploy a working MCP server for a Board data source, with authentication and gateway registration, from a starter template to a running endpoint on the platform
• Implement a RAG ingestion and retrieval pipeline on PostgreSQL with pgvector and measure its retrieval quality against a defined test set
• Write and run a GitLab CI pipeline that builds a container image, executes automated tests, and deploys to the Kubernetes platform through ArgoCD
• Author Terraform and Ansible changes to the platform's infrastructure and configuration, delivered through merge requests and code review
• Apply the platform's security controls (OAuth 2.0 audience‑bound tokens, deny‑by‑default authorization, secrets management, audit logging) to the connector they build
• Produce a developer quick‑start guide and present the completed work to the AIS team and SI/AI Program

While completing these learning objectives, the intern will gain hands‑on experience with Python, Kubernetes, AWS, Terraform, Ansible, GitLab CI, ArgoCD, PostgreSQL with pgvector, and the Model Context Protocol; gain a working understanding of how a regulated institution governs SI/AI access to enterprise data; and help determine whether a career in SI/AI platform or infrastructure engineering is of interest upon graduation.

Previous Intern Projects

Previous interns on the SI/AI Program and connectors work had the opportunity to contribute to projects such as

• Drafting the product canvas for the Board's governed RAG platform
• Prototyping MCP servers for economic data sources, including FRED and Haver
• Evaluating hosting options and documenting architecture decisions
• Standing up a PostgreSQL and pgvector replica of a Board data repository for retrieval use cases
• Testing SI/AI connector authentication paths end to end with Claude Code
• Building GitLab CI and Ansible automation for server provisioning and patching

Through these projects, you will work with infrastructure engineers, database administrators, cloud architects, and data scientists across the Board.

How You'll Make an Impact

Our mission matters. It includes promoting a strong economy for the American people by fostering stability, integrity, and efficiency of the nation's monetary, financial, and payment systems. As an intern at the Federal Reserve Board, you will have the opportunity to contribute to this mission. The connectors you help build are what let economists, analysts, and Board leaders put SI/AI to work on real Board data, safely.

The IT Internship requires enrollment in or soon beginning an accredited graduate‑level program pursuing a degree in Computer Science, Computer Engineering, Software Engineering, Artificial Intelligence, Data Science, Information Systems, Cybersecurity, or a related field of study; graduating August 2027 or later with a minimum 3.0 GPA.

While completing these learning objectives, the intern will gain hands‑on experience with Python, Kubernetes, AWS, Terraform, Ansible, GitLab CI, ArgoCD, PostgreSQL with pgvector, and the Model Context Protocol; gain a working understanding of how a regulated institution governs SI/AI access to enterprise data; and help determine whether a career in SI/AI platform or infrastructure engineering is of interest upon graduation.

Previous Intern Projects

Previous interns on the SI/AI Program and connectors work had the opportunity to contribute to projects such as

• Drafting the product canvas for the Board's governed RAG platform
• Prototyping MCP servers for economic data sources, including FRED and Haver
• Evaluating hosting options and documenting architecture decisions
• Standing up a PostgreSQL and pgvector replica of a Board data repository for retrieval use cases
• Testing SI/AI connector authentication paths end to end with Claude Code
• Building GitLab CI and Ansible automation for server provisioning and patching

Through these projects, you will work with infrastructure engineers, database administrators, cloud architects, and data scientists across the Board.

Qualifications

Overview of Division, Section and Team: The Division of Information Technology delivers the Board's technology services. The Application Infrastructure Support (AIS) unit, in the Compute and Storage Infrastructure Branch, runs the middleware, database, and application hosting platforms that Board applications depend on, and is building the governed hosting platform for SI/AI connectors (MCP servers), RAG services, and the identity, gateway, and inventory controls around them. The intern joins a small team of engineers and architects working in partnership with the Board's SI/AI Program.

Expected Projects

• Build one MCP server for a Board data source, from template through deployment on the platform, with authentication and gateway registration
• Implement or extend a RAG ingestion and retrieval pipeline on PostgreSQL with pgvector
• Deliver platform infrastructure and configuration changes through Terraform, Ansible, and GitLab CI pipelines
• Contribute to the MCP connector inventory and self‑service catalog
• Produce a developer quick‑start guide for building MCP servers to Board standards

Suggested Major/Minor: Computer Science, Computer Engineering, Software Engineering, Artificial Intelligence, Data Science, Information Systems, Cybersecurity

Required Skills And Knowledge

• Programming in Python
• Working knowledge of large language model tooling and concepts: prompting, tool calling, embeddings, and retrieval‑augmented generation
• Familiarity with infrastructure as code and CI/CD practices: Ansible, Terraform, GitLab CI or an equivalent pipeline tool
• Working knowledge of Linux, Git, and containers (Docker or equivalent)
• Understanding of REST APIs, JSON, relational databases, and SQL
• Ability to write clear technical documentation

Preferred Skills

• Kubernetes (deployments, services, Helm or Kustomize) and GitOps tools such as ArgoCD
• AWS fundamentals (IAM, EKS, Secrets Manager)
• Hands‑on experience with the Model Context Protocol or building tools for SI/AI agents
• Vector databases (pgvector, Chroma, or similar) and RAG frameworks (LangChain, LlamaIndex, or similar)
• OAuth 2.0 and OpenID Connect concepts; exposure to Keycloak or Okta
• Experience using SI/AI coding assistants (Claude Code, Copilot, or similar) and validating their output

Required Documents for application: A copy of an unofficial transcript may be requested. Resume required.

Notes: US Citizenship is required. Applicants must be current students, graduating from their program August 2027 or later. Proof of enrollment will be required.

Keywords: AI, SI, super intelligence, artificial intelligence, SI/AI, AI/SI, LLM, MCP, Model Context Protocol, RAG, retrieval‑augmented generation, AI agents, AI connectors, Python, Kubernetes, EKS, AWS, Terraform, Ansible, GitLab CI, CI/CD, GitOps, ArgoCD, pgvector, PostgreSQL, OAuth, platform engineering, DevOps, infrastructure, systems engineer.

Job Type

Intern (Fixed Term)

Job Exempt

No

Relocation Provided

No

Compensation Grade(s)

FH Pay Grade 20 - FH Pay Grade 22

Pay

$26.68 - $28.37

Rehabilitation Act

The Board complies with the Rehabilitation Act of 1973, as amended, and provides job applicants with disabilities reasonable accommodations to assist them in applying for jobs at the Board. If you have a disability and would like to request an accommodation in order to apply for a job at the Board, please call 202-452-3880 or e-mail [e-mail].

Equal Opportunity Employer

We are an Equal Opportunity Employer and do not discriminate against any employee or applicant for employment on the basis of race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, genetic information, or application, membership, or service in the uniformed services.

Privacy

You may review the Federal Reserve Board's Privacy Act Notice at https://www.federalreserve.gov/careers/files/fr1273.pdf.

Paperwork Reduction Act

OMB No. 7100-0181

Approval Expires October 31, 2029

Public reporting burden for this collection of information is estimated to average 0.26-0.71 hours per response, including the time to gather and maintain data in the required form and to review instructions and complete the information collection. Send comments regarding this burden estimate or any other aspect of this collection of information, including suggestions for reducing this burden to: Secretary, Board of Governors of the Federal Reserve System, Washington, DC 20551; and to the Office of Management and Budget, Paperwork Reduction Project (7100–0181), Washington, DC 20503. The Federal Reserve may not conduct or sponsor, and an organization (or a person) is not required to respond to a collection of information unless it displays a currently valid OMB control number.