Software Engineer Intern, Conversational AI (Alfie)
About The Position
Alfie is Pebl’s proprietary conversational AI — built in-house and live across our product, our self-serve flow, and hellopebl.com. Alfie doesn’t just answer questions; it takes action, surfaces insights, and guides users toward what they actually need. It’s one of the most visible parts of our product and a direct factor in how we win enterprise deals. The Conversational AI engineering team owns the full stack behind Alfie: the model integrations, retrieval and context systems, evaluation infrastructure, and the APIs that surface Alfie’s capabilities across Pebl’s platform. This summer, you’ll work directly alongside senior engineers on systems that are live, customer-facing, and under active development. You’ll be hands-on with the hardest open problems on the team: how do we measure and systematically improve Alfie’s response quality? How should our retrieval pipeline handle edge cases? Where are the latency and reliability bottlenecks, and how do we fix them? Your work will ship to a live product and have real impact on users and business outcomes. This is a 12-week internship in Palo Alto, CA.
Requirements
- Currently pursuing a BS or MS in Computer Science, Machine Learning, or a related field (or equivalent hands-on experience)
- Strong foundation in Python — you’re comfortable writing production-quality code, not just notebooks
- Working knowledge of LLMs and how they're used in real systems — you understand context engineering, agent harnesses, tool use, and how model behavior is shaped by what gets passed in and when.
- Experience building or debugging backend services; REST APIs and async patterns are familiar territory
- A habit of building with AI tools, not just reading about them
Nice To Haves
- Exposure to ML evaluation methods, testing frameworks, or observability tooling is a plus
Responsibilities
- Contributing meaningfully to Alfie’s core AI stack — working across model integrations, context management, prompt systems, and the retrieval pipeline that feeds Alfie accurate, grounded responses.
- Playing an active role in evaluation tooling: helping develop automated test suites, quality scorecards, and regression harnesses that let us measure Alfie’s performance and ship improvements with confidence.
- Helping diagnose reliability and latency issues in production — tracing calls, profiling bottlenecks, and contributing fixes that improve system stability and scale.
- Working closely with the PM and engineering team to understand product requirements and contribute to the technical implementation.
- Contributing to internal AI tooling (Athena, Pebl’s employee-facing AI) on similar infrastructure and evaluation problems.
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What This Job Offers
Career Level
Intern
Education Level
Associate degree
