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What you'll do

• Build an agent quality evaluation pipeline: an automated benchmark measuring response accuracy, grounding, and hallucination rate

• Run retrieval tuning experiments, improving chunking, embedding, and ranking strategies validated against the benchmark

• Build a working GraphRAG/memory prototype for cross-session memory persistence

• Document experiments and findings so the core team can adopt them directly

We're looking for someone who

• Solid Python and software engineering fundamentals (final-year student or fresh graduate level)

• Familiarity with LLMs, prompt engineering, and loop engineering; hands-on exposure to RAG concepts is a strong plus

• Basic data engineering skills — building pipelines, working with structured and unstructured data (e.g. JSON)

• Experience with LangChain/LlamaIndex, graph databases, or evaluation frameworks (e.g. Ragas, DeepEval) is a strong plus

• Self-directed learner, comfortable with ambiguity, with an experimentation mindset — always willing to try a new retrieval or memory approach rather than sticking to the first one that works

• Good written English for documentation, since findings need to be picked up by the core engineering team, including honest reporting of benchmark results, regressions included

• Genuinely into how AI agents actually work, not just running pre-built tutorials

• Currently pursuing or recently completed a Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related field (final-year student or fresh graduate)

Why you'll love interning here

• Real projects. Real ownership. No coffee runs. No photocopying. You'll contribute to work that actually matters.

• Learn from experts. Work alongside experienced professionals who genuinely enjoy mentoring.

• Grow faster. Receive regular feedback, ask questions freely, and learn through doing.

• Meet amazing people. Collaborate across teams and build meaningful connections.

• Get paid while you learn. Competitive monthly internship allowance.

• Experience global SaaS. Discover how a fast-growing tech company builds products used by teams around the world.