AI Engineer

Summary

Guidewire is seeking an AI Engineer to join our Professional Services AI Engineering team in Bangalore. 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.

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. This role suits someone who has solid AI fundamentals and is excited to go deep on agent and prompt design as their day job.

Job Description

Key Responsibilities

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. Use frameworks like LangChain LlamaIndex or LangGraph where they fit; write custom orchestration where they dont.

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 & Experience

Education: Bachelors or Masters degree in Computer Science Data Science Statistics or a related technical field.

Experience: 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.

Preferred Skills & Experience

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.

About Guidewire

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 and follow us on Twitter: @GuidewirePandC.

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 its applicable to the position.