Associate Software Engineer

About the Role

Duck Creek Technologies is seeking early-career engineers to join an AI engineering team focused on building LLM-based systems. This role involves evaluating the correctness of AI/LLM system outputs and modeling extracted information as structured knowledge for trustworthiness and queryability.

Key Responsibilities

• Build and extend LLM evaluation harnesses (golden datasets, precision/recall/F1, calibration, LLM-as-judge scoring).
• Design and work with knowledge graphs (entity-relationship modeling, graph traversal/queries, embeddings-based similarity and retrieval).
• Build GenAI/LLM pipelines in Python (prompting, RAG, structured output).
• Write clean, tested code.
• Collaborate with senior engineers.
• Document your work.
• Act in accordance with Duck Creek Technologies' mission, vision, and core values.

Requirements & Tech Stack

• Strong Python fundamentals.
• Solid grasp of data structures & algorithms.
• Working understanding of LLM fundamentals: prompting, embeddings, RAG, basic evaluation concepts.
• A maintained personal GitHub profile with at least one substantive AI/LLM project (academic or personal).
• Share resume along with GitHub profile link.

Qualifications

• B.Tech/M.Tech with an AI/ML specialization, or CS/IT with strong, demonstrable AI coursework/projects.
• 0 to 2 years of experience.

Good To Have

• Exposure to evaluation frameworks/metrics for generative AI (e.g. Ragas, DeepEval, or a self-built LLM-judge approach).
• Exposure to knowledge graphs / graph data structures (NetworkX, Neo4j, RDF/OWL, or a custom graph model).
• Any agent framework (LangChain/LangGraph or similar).
• Vector databases.
• Any cloud platform.
• REST API basics (FastAPI/Flask).