AI Architect

Summary

Guidewire is seeking an AI Architect to join our Professional Services AI Engineering team in Bangalore. You will work horizontally across AI Engineering initiatives helping blueprint AI features and define the patterns that allow Strike Teams to deliver production-ready AI capabilities. Your primary craft is AI solution architecture shaping the prompt engineering harness engineering RAG evaluation observability and model-selection approach that turns an AI idea into a reliable feature.

You will help teams make data-informed decisions about when to use agentic workflows direct LLM calls RAG classical NLP/NLU lightweight ML or model fine-tuning. You will mentor P2/P3 AI engineers review designs create reusable patterns and help the broader team explain AI design choices clearly across Guidewire SI partners and customers.

Job Description

Key Responsibilities

• AI Feature Blueprinting: Create technical blueprints for AI features including architecture data needs model strategy evaluation approach and delivery risks.
• Model Selection: Define patterns for identifying which LLM model should be used for each call and when to use NLP/NLU instead.
• Harness Architecture: Shape reusable patterns for agent loops tool/function calling context construction memory structured outputs retries and failure handling.
• Prompt Engineering: Set standards for prompt design versioning review experimentation and regression testing as first-class engineering assets.
• Evaluation: Design eval frameworks golden datasets regression suites error analysis and LLM-as-judge patterns to measure quality and guide decisions.
• RAG & Knowledge Patterns: Guide document parsing chunking embeddings retrieval reranking prompt assembly and grounded response patterns.
• Mentorship & Enablement: Coach P2/P3 AI engineers review technical designs create examples and help junior engineers present architecture findings clearly.
• Cross-Guidewire Collaboration: Partner with Product AI CoE PS customer teams and SI partners.

KPIs & Success Metrics

• AI feature blueprints are clear reusable and actionable for Strike Teams.
• Model and architecture choices are backed by evals analysis and documented trade-offs.
• Prompt harness RAG and evaluation patterns are adopted consistently by P2/P3 engineers.
• Delivered AI features meet project bars for accuracy groundedness reliability latency and cost.
• Junior and mid-level engineers can implement patterns and explain the results confidently.

Key Skills & Experience

• Education: Bachelors or Masters degree in Computer Science Data Science Statistics Machine Learning Engineering or a related technical field.
• Experience: 8 years of experience in AI machine learning data science software engineering or solution architecture.
• AI Architecture: Strong ability to translate ambiguous product or delivery goals into practical AI system designs.
• AI Fundamentals: Deep understanding of LLMs prompts embeddings retrieval structured outputs tool use agentic workflows and model failure modes.
• NLP/NLU Judgment: Able to recognize when classical NLP/NLU rules-based approaches lightweight ML or structured extraction are better than generative AI.
• Technical Proficiency:
  • Strong Python/Java skills and ability to read review and contribute to production-quality code.
  • Experience designing LLM harnesses including orchestration tool/function calling context construction retries and fallback behavior.
  • Strong prompt engineering practice including structured iteration versioning evaluation and regression testing.
  • Working knowledge of RAG patterns embeddings retrieval evaluation and vector search concepts.
  • Comfortable designing evaluation approaches using golden sets regression suites error taxonomies and human review loops.
• Engineering Excellence: Familiar with Git code review testing CI/CD concepts cloud-based delivery and production engineering practices.
• Communication & Mentorship: Able to explain complex AI trade-offs clearly and coach less experienced engineers without direct reporting authority.

Preferred Skills & Experience

• Agentic AI Systems: Experience with agentic frameworks or custom agent harnesses in production.
• Evals: Experience building structured eval harnesses regression suites LLM-as-judge patterns or production feedback loops.
• Cloud: Hands-on AWS experience with services such as Bedrock SageMaker OpenSearch or related cloud-native AI/data services.
• Fine-Tuning: Experience evaluating or implementing model fine-tuning distillation or domain adaptation.
• Guidewire Knowledge: Familiarity with Guidewire products or the insurance domain is a plus.
• Enterprise AI Delivery: Prior experience working on document-heavy regulated insurance finance or professional services 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.