Summer/Fall 2026 - AI Engineering Internship

About Us

We’re continuing to build a transformative healthcare accreditation platform that is revolutionizing how our clients and new hospitals manage compliance, quality improvement, and regulatory processes. Our platform combines cutting-edge technology with deep healthcare domain expertise to solve real problems for healthcare organizations nationwide.

The Opportunity

The goal is to have interns turn into full time employees; Therefore, you will be given full time responsibilities day one. To add onto that, you will be working in a high velocity growth startup and will be required to move fast. You’ll work directly with our engineering team on a production healthcare platform, gaining hands-on experience with enterprise-grade systems while making real contributions that impact our product and customers.

Compensation Structure

Base position is unpaid, however qualified candidates may receive upfront equity compensation based on their experience level and demonstrated capabilities. We evaluate each applicant individually and offer equity packages commensurate with their potential contribution.

About the Role

We’re hiring for an AI Engineer. To be considered, you must have a deep expertise in a focus and some knowledge of the latter.

Requirements

• Deep specialization in one of these areas: Agentic AI (Claude Agent SDK, MCP Servers, Tool Use) + Node.js/TypeScript + AWS + RAG

• Strong understanding of modern practices and version control (Git)

• Ability to work collaboratively within a specialized team structure

• Passion for building production-ready, scalable systems

Nice to Have

• Experience working in team environments with separated responsibilities

• Understanding of production AI deployment

• Experience with Claude Code, MCP server development, or agentic AI frameworks

• Previous experience with healthcare or regulated industries

What You’ll Build

• Agentic AI systems: Autonomous agents using Claude Agent SDK, MCP servers, and tool use for domain-specific workflows, combined with RAG for knowledge retrieval via Bedrock

• Node.js API services: Production AI inference endpoints and services integrated into our existing Node.js/MongoDB platform + Voyage AI vector database management

• AWS AI services: Lambda-based inference, Bedrock integration

• Semantic search & MCP integrations: Knowledge extraction and contextual Q&A systems using S3 Vectors, Mongo DB Atlas and OpenSearch (hybrid search), exposed via MCP servers for agent consumption

Key Responsibilities

• Conduct exploratory data analysis to identify patterns in complex healthcare datasets

• Build agentic AI systems using Claude Agent SDK, MCP servers, and tool use, alongside RAG pipelines with AWS Bedrock and vector databases

• Manage vector databases: Mongo DB/S3 Vectors

• Develop document processing pipelines for text extraction and analysis

• Create production Node.js services for real-time AI inference, integrated with our MongoDB data layer

• Implement semantic search and knowledge extraction from document repositories

• Design Lambda-based inference systems on AWS

• Integrate LLMs via agentic frameworks (Claude Agent SDK, MCP) for domain-specific autonomous workflows and Q&A systems

• Develop ETL processes for external data sources and APIs

Required Qualifications

Candidates must meet all Core Qualifications.

Core Qualifications

• Node.js/TypeScript programming skills

• Git for version control

• Understanding of deployment and production systems

• Collaborative development workflows

AI/ML Development

• Experience building production AI services in Node.js/TypeScript

• 1+ years with AWS services (Lambda, Bedrock, S3, EC2) and agentic AI frameworks (Claude Agent SDK, MCP servers, tool use)

• RAG development experience with vector databases

• NLP/Document processing expertise (text extraction, classification, information retrieval)

Nice to Have

• Healthcare or regulated industry experience

• Experience with Claude Code and agentic development workflows

• Experience with Hugging Face transformers and LLMs

• MongoDB experience and familiarity with aggregation pipelines

• Time-series forecasting and anomaly detection

• Advanced statistical modeling (survival analysis, propensity scoring)

• Knowledge of data privacy and compliance frameworks

Technical Stack

AI/ML Development: Node.js/TypeScript, AWS (Bedrock, Lambda, S3, EC2), Agentic AI (Claude Agent SDK, MCP Servers, Tool Use, Claude Code), MongoDB, Vector Databases (S3 Vectors, OpenSearch), NLP libraries (sentence-transformers), Git

Our Hiring Process

We believe in a transparent and thorough selection process that respects your time while ensuring mutual fit:

Initial Screening Call

We’ll discuss your background, experience, and career goals, while providing an overview of the role and our team culture.

Technical Challenge (issued on case by case basis)

You’ll receive a real-world technical challenge to complete within a specified timeframe. We encourage you to leverage all available resources—including AI tools, documentation, and libraries—just as you would in a production environment. This reflects how we actually work and allows you to showcase your problem-solving approach.

Technical Interview

We’ll have an in-depth discussion about your solution and explore related technical concepts. You should be prepared to walk through every aspect of your submission—explaining architectural decisions, code logic, trade-offs, and potential improvements. Whether you wrote the specific code section manually or generated it with AI assistance, you must demonstrate complete ownership and understanding of the entire codebase. This is a production-level assessment: we expect you to discuss, debug, and defend your work as if it were going live tomorrow.

We’re looking for engineers who can think critically, adapt their approach, and truly understand the systems they build—not just those who can generate code.

Ready to apply? We look forward to hearing from you!

MedLaunch is an equal opportunity employer committed to diversity and inclusion.