Company Overview:
We're on a mission to make every sales manager a better coach. We serve sales teams - much like they serve customers. Our AI Performance Agents diagnose drivers of rep performance, personalize manager-rep coaching, and accelerate individual performance by up to 20%, surfacing needle-moving insights on rep attributes, competencies, activities, and time allocation.
The product is beautiful, intuitive, and personalized for every sales executive, manager, and rep at mid-market companies. The buyers are Sales, Enablement and RevOps leaders who care deeply about their people - helping reps grow instead of letting them go.
Our team is guided by principles of deep-rooted empathy for sales teams. We’re remote-first and currently focused on serving U.S.-centric customers.
Position Overview:
We are seeking a motivated AI Engineering Intern to join our team for the summer. This is a hands-on, project-driven role at the intersection of Generative AI, data engineering, and applied ML. The intern will work directly alongside our engineering team on real product challenges - building agentic pipelines, RAG systems, and LLM-powered features that ship to customers.
The ideal candidate has strong programming fundamentals (Python, JavaScript/Node.js, or React), a genuine curiosity about AI and LLMs, and the drive to learn fast in a fast-moving startup environment. Prior experience with GenAI frameworks and the right mindset is an absolute requirement.
Duration: 60-90 days (Unpaid)
Location: Remote (US based Only)
What to expect working at PeopleLens:
This is a Pro-bono full time summer internship, with a focus on:
- Build real things. Your work will ship into our product and be used by actual customers.
- Learn how to become hirable at world-class tech organizations working on AI.
- Take on real ownership of meaningful features and engineering challenges.
- Earn references that reflect your performance and initiative.
- Build a network across startups and emerging AI technologies.
Key Responsibilities:
Agentic AI & LLM Engineering
- 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
Data Engineering & ML
- 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
Across All Areas
- 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
Qualifications:
Required
- 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
Preferred
- 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