AI Engineer

Role overview

AI Engineer at Guidewire

Harness Engineering: Build and maintain the LLM harnesses that power each AI feature — agent loops, tool/function calling, context construction, memory, retries, and failure handling.

Responsibilities

• You will help shape the technical approach alongside our AI Architect and partner with a Senior AI Engineer on the deeper architectural calls, contributing your own ideas and knowing when to bring in specialist support.
• Use frameworks like LangChain, LlamaIndex, or LangGraph where they fit; write custom orchestration where they don't.
• Prompt Engineering: Design, iterate, and version prompts as first-class assets.
• Run structured prompt experiments, measure deltas with eval datasets, and keep prompt libraries clean and reviewable.
• RAG Pipelines: Build and operate Retrieval-Augmented Generation pipelines that extract information from documents and parse it into structured knowledge bases — chunking, indexing, retrieval, reranking, prompt assembly, and response handling — collaborating with the AI Architect to shape and refine the patterns.
• Embeddings & Vector Indexes: Generate embeddings and manage vector indexes (e.g., OpenSearch, Pinecone, pgvector).
• Tune indexes for retrieval quality and cost.
• Data Parsing & Curation: Build extraction and parsing pipelines for documents, structured records, and customer datasets so they are clean, labeled, and ready for downstream AI work.
• Accuracy Validation: Write and operate accuracy validation scripts.
• Maintain evaluation datasets and report quality metrics to the Strike Team and the AI Architect.
• Light ML Work: Apply traditional ML where appropriate — classification, clustering, lightweight fine-tuning — to complement LLM-based components.
• Analysis: Do the data analysis that informs AI design decisions — sample inspection, error analysis, prompt iteration.
• KPIs & Success Metrics
• AI feature accuracy and quality against eval datasets meets the project bar.
• Prompt iteration velocity with measurable eval deltas on owned features.
• RAG and retrieval quality (relevance, groundedness) for owned pipelines.
• On-time delivery of AI-side Strike Team commitments.
• Eval coverage: golden and regression sets maintained for owned features.
• Key Skills &

Required qualifications

• Bachelor's or Master's degree in Computer Science, Data Science, Statistics, or a related technical field.
• 3+ years of AI or data science experience, with hands-on time in LLM-based application development.
• Technical Proficiency:
• – Strong Python skills, including the standard data science stack (pandas, numpy, scikit-learn).
• – Hands-on experience building LLM harnesses — agent loops, tool/function calling, structured outputs — against APIs like Anthropic, OpenAI, or Bedrock.
• – Strong prompt engineering practice: structured iteration, prompt versioning, and prompt evaluation against datasets.
• – Working experience with at least one orchestration framework (LangChain, LlamaIndex, LangGraph) and at least one vector database.
• – Comfortable with embeddings, similarity search, and basic retrieval evaluation.
• – Working knowledge of classical ML for analysis and lightweight modeling tasks.
• – Comfort using AI coding assistants (Claude Code) for daily work.
• Engineering Excellence: Able to write clean, tested code that ships to production — not just notebooks.
• Familiar with Git, code review, and basic CI/CD.
• Analytical Mindset: Strong instinct for data analysis, error inspection, and iterative experimentation.
• Agent Frameworks: Hands-on experience with agentic frameworks (LangGraph, Claude Agent SDK, OpenAI Agents) or custom agent harnesses in production.
• Evals: Experience building structured eval harnesses (golden sets, regression suites, LLM-as-judge patterns).
• Cloud: Hands-on AWS experience (Bedrock, SageMaker, OpenSearch).
• Fine-Tuning: Any experience with model fine-tuning or distillation.
• Guidewire Knowledge: Familiarity with Guidewire products or the insurance domain is a plus.
• Domain Analysis: Prior experience working on document-heavy, regulated, or insurance/finance datasets.

Preferred qualifications and skills

• &

Employment details

• Location: India - Bangalore

About the employer

• Guidewire is seeking an AI Engineer to join our Professional Services AI Engineering team in Bangalore.
• Guidewire is the platform P&C insurers trust to engage, innovate, and grow efficiently.
• We combine digital, core, analytics, and AI to deliver our platform as a cloud service.
• More than 540+ insurers in 40 countries, from new ventures to the largest and most complex in the world, run on Guidewire.
• As a partner to our customers, we continually evolve to enable their success.
• We are proud of our unparalleled implementation track record with 1600+ successful projects, supported by the largest R&D team and partner ecosystem in the industry.
• Our Marketplace provides hundreds of applications that accelerate integration, localization, and innovation.
• For more information, please visit www.guidewire.com and follow us on Twitter: @Guidewire_PandC.
• Guidewire Software, Inc. is proud to be an equal opportunity and affirmative action employer.
• We are committed to an inclusive workplace, and believe that a diversity of perspectives, abilities, and cultures is a key to our success.
• Qualified applicants will receive consideration without regard to race, color, ancestry, religion, sex, national origin, citizenship, marital status, age, sexual orientation, gender identity, gender expression, veteran status, or disability.
• All offers are contingent upon passing a criminal history and other background checks where it's applicable to the position.
• Guidewire is proud to be a disability inclusive employer.
• We are committed to providing individualized accommodations and support to candidates for any part of our hiring process.
• If you think you may need disability-related accommodations, please email EmployAbility at accommodations-gw@employ-ability.org.uk, our disability partner, or schedule a call with an EmployAbility expert (calendar booking slot) for a confidential conversation.

Additional role details

• Summary
• You will work as a dedicated AI-side member of a Strike Team, pairing with a Product Engineer to deliver AI productization projects end-to-end.
• Your primary craft is harness engineering and prompt engineering — building the agent harnesses, tool integrations, prompts, and eval loops that turn an LLM into a production feature.
• Around that core, you will also handle the supporting AI work: data parsing, embeddings, RAG pipelines, light ML work, and accuracy validation.
• This role suits someone who has solid AI fundamentals and is excited to go deep on agent and prompt design as their day job.