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Duck Creek Technologies

Associate Software Engineer (AI)

About this role

Duck Creek Technologies provides a SaaS platform for property and casualty insurers. This Bengaluru role is in an AI engineering team building LLM-based systems, with a focus on checking whether AI output is correct and on modelling extracted information as knowledge graphs. You build LLM evaluation tooling and GenAI pipelines in Python, and write tested code alongside senior engineers. It suits early-career engineers with 0-2 years of experience and a real AI/LLM project on GitHub. Applications without a working GitHub link showing original project work are not considered.

Duck Creek Technologies is hiring for Associate Software Engineer (AI), a full-time role based in Bengaluru.

Who can apply: 0–2 years. Skills: Python, LLM evaluation, RAG, Knowledge graphs, Prompting.

Hirastra checked that this opening is live. Apply directly through the official posting; applying is always free.

What you'll do

  • Build and extend LLM evaluation harnesses, including golden datasets, precision/recall/F1, calibration and LLM-as-judge scoring
  • Design and work with knowledge graphs, including entity-relationship modelling, graph queries and embeddings-based retrieval
  • Build GenAI/LLM pipelines in Python covering prompting, RAG and structured output
  • Write clean, tested code, collaborate with senior engineers and document your work

What you need

  • B.Tech/M.Tech with AI/ML specialization, or CS/IT with strong AI coursework or projects, and 0 to 2 years of experience
  • Strong Python fundamentals and solid grasp of data structures and algorithms
  • Working understanding of LLM fundamentals: prompting, embeddings, RAG and basic evaluation
  • Maintained GitHub profile with at least one substantive original AI/LLM project
  • Resume must include the GitHub profile link
Location
Bengaluru
Work mode
See listing
Experience
0–2 years
Pay
₹8–15 LPA (Est.)
Type
Full-time job, AI & ML
Added
29 October 2026

Skills

  • Python
  • LLM evaluation
  • RAG
  • Knowledge graphs
  • Prompting

"Est." = Hirastra's estimate based on market data, not an official figure.

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