PeopleLensRemote
AI Engineering Intern (Summer 2026)
United States of America
Internship
3 hours ago
No H1B
Key skills
PythonReactJavaScriptNode.jsGitREST APIsSQLSoftware engineering fundamentalsGenerative AILarge Language Models (LLMs)LangChainLangGraphLlamaIndexRetrieval-Augmented Generation (RAG) pipelinesPineconeChromaWeaviateModel Context Protocol (MCP)Prompt engineeringFew-shot designLLM evaluationCloud platforms GCPCloud platforms AWSCloud platforms AzurePostgreSQLMongoDBBias toward actionNoSQLAIMLNLPGenAILLMGeminiRAGAgenticETLData EngineeringAWSAzureGCPVertex AINeo4jSalesforceCRMCommunicationSales
About this role
PeopleLens is dedicated to enhancing sales team performance through innovative AI solutions. They are seeking an AI Engineering Intern for the summer to work on projects involving Generative AI, data engineering, and applied ML, contributing to real product challenges and building features that will be used by customers.
Responsibilities:
- Design and implement LLM-powered agentic workflows using frameworks like LangGraph, LangChain, or similar
- Build and evaluate RAG (Retrieval-Augmented Generation) pipelines with vector databases (e.g., Pinecone)
- Develop and optimize prompts, system instructions, and evaluation harnesses for AI agents
- Prototype MCP (Model Context Protocol) server integrations to connect AI agents with external data sources
- Contribute to our AI agent infrastructure on GCP/Vertex AI using Gemini models
- Build and maintain scalable data pipelines, ETL workflows, and AI-ready feature engineering scripts that feed downstream LLM and ML models
- Clean, normalize, and structure sales performance data (CRM, enablement platforms) for use in RAG pipelines, vector stores, and AI-driven coaching models
- Support ML and GenAI model development - including data prep, embedding generation, correlation analysis, and experiment tracking with LLM evaluation harnesses
- Develop and optimize SQL queries, data transformation scripts, and automation processes that power AI agent context and retrieval workflows
- Collaborate with senior engineers and data scientists to gather requirements and ship solutions
- Document workflows, prompt libraries, agent designs, and engineering best practices
- Participate in design reviews, sprint demos, and async team standups
Requirements:
- Pursuing a degree in CS, Data Science, AI/ML, or a related field
- Proficient in Python and/or React, JavaScript, Node.js
- Familiar with Git, REST APIs, SQL, and software engineering fundamentals
- Genuine interest in GenAI, LLMs, and agentic systems
- Hands-on experience with LLM frameworks (LangChain, LangGraph, LlamaIndex, or similar)
- Built or experimented with RAG pipelines and vector databases (Pinecone, Chroma, Weaviate, etc.)
- Familiarity with MCP and agentic tool-use patterns
- Prompt engineering, few-shot design, or LLM evaluation experience
- Strong communication skills, self-directed learning, and a bias toward action
- Experience with React/Node.js
- Exposure to cloud platforms (GCP, AWS, or Azure), especially AI/ML services
- Experience with relational (SQL/PostgreSQL) and NoSQL (MongoDB) databases
- ML, NLP, or data science coursework/projects
- Familiarity with Salesforce, Gong, or similar CRM/sales enablement tools
- Experience with graph databases (Neo4j) or structured data pipelines
- Open-source AI/ML contributions
- Previous technical internship experience