Senior ML Engineer, Generative AI

Guidewire Software, Inc.

Job Overview

Location

United States - Remote

Job Type

Full-time

Full Job Description

📋 Description

• Lead the design, implementation, and evolution of Guidewire’s GenAI and LLM products, including data ingestion, feature pipelines, model training, fine-tuning, deployment, and monitoring on AWS (e.g., S3, EC2, RDS, SageMaker).
• Architect and build robust ML/LLM pipelines that power high-impact use cases such as claim summarization, underwriting assistance, pricing and rating intelligence, and developer productivity tools across the product portfolio.
• Develop and optimize LLM solutions using techniques such as prompt engineering, retrieval-augmented generation (RAG), vector databases, and fine-tuning to deliver reliable, safe, and high-performing experiences for insurance users.
• Collaborate with Product Strategy, PDO, and Professional Services teams to align GenAI capabilities with the broader Product VPMOM, Agentic AI product roadmap, and customer adoption goals.
• Establish and apply ML Ops best practices for CI/CD, experimentation, evaluation, observability, and responsible AI, ensuring models are auditable, secure, and production-ready at scale.
• Mentor and coach engineers and data scientists, conduct code and design reviews, and champion technical excellence, including performance, reliability, and cost efficiency of AI workloads.
• Partner with cross-functional teams (Security, Finance, BizTech, GTM) to ensure AI solutions adhere to data governance and security controls, and contribute to Guidewire’s mission to transform how P&C insurers do business through cloud, analytics, and AI.
• Foster a culture of curiosity, innovation, and responsible use of AI—empowering teams to continuously leverage emerging technologies and data-driven insights to enhance productivity and outcomes.

🎯 Requirements

• 5+ years of professional experience in Machine Learning and/or Data Science, including end-to-end delivery of production ML systems.
• Deep expertise in Python and experience building scalable ML/LLM services and pipelines, ideally on AWS using services such as S3, EC2, RDS, and SageMaker.
• Strong understanding of ML Ops practices for model development, deployment, monitoring, and lifecycle management (including CI/CD for ML, experiment tracking, model registries, and drift detection).
• Hands-on experience with classical and gradient-boosting models (such as GLM, Random Forest, and XGBoost) and their application to real-world business problems.
• Deep understanding of neural networks and transformer-based architectures for LLMs and chat models, including familiarity with open-source foundation models and their fine-tuning and inference.
• Experience with prompt engineering, RAG and related LLM architecture patterns, and vector databases for semantic search and retrieval.
• Solid knowledge of evaluating and monitoring LLM performance using NLP and LLM-assisted metrics, with a focus on safety, robustness, and user experience.
• Demonstrated technical leadership: driving design decisions, leading complex engineering efforts, mentoring peers, and conducting thoughtful code and architecture reviews.

🏖️ Benefits

• Flexible work environment.
• Health and wellness benefits.
• Paid time off programs including volunteer time off.
• Market-competitive pay and incentive programs.
• Continual development and internal career growth opportunities.
• Participation in in-person orientation process to build connection, collaboration, and shared understanding of Guidewire’s mission.

Skills & Technologies

Python

AWS

Docker

Kubernetes

Data Science

Senior

Remote

$160k-240k

Degree Required

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Guidewire Software, Inc.

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About Guidewire Software, Inc.

Guidewire Software, Inc. provides core technology platforms to property and casualty insurers worldwide. The company’s cloud-based InsuranceSuite combines policy administration, billing, and claims management with digital engagement and analytics tools. Headquartered in San Mateo, California, Guidewire serves more than 540 insurers across 42 countries, enabling them to streamline operations, launch products faster, and improve customer experience through open APIs and data-driven insights.

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