Staff Software Engineer

Guidewire Software•San Mateo, CA

10d•$158,000 - $277,000•Remote

About The Position

Summary Solution Engineering is looking for a Staff Software Engineer to provide technical leadership across cloud-native services and AI-enabled engineering initiatives. This role is ideal for someone who thrives in a hands-on engineering environment, enjoys solving complex distributed systems problems, and can guide multiple teams toward secure, scalable, and reliable solutions. You will help design, build, and operate multi-tenant SaaS services and platform capabilities that create measurable customer and business value. You will partner closely with engineering, product, architecture, security, and field-facing teams to deliver these solutions. This is a technical leadership role requiring strong engineering depth, sound architectural judgment, mentorship, and the ability to drive execution in a fast-paced, collaborative environment.

Requirements

12+ years of software engineering experience, ideally with a focus on cloud platforms, data platforms, distributed systems, SaaS, or platform engineering.
Deep expertise in Java and strong proficiency in designing and building large-scale distributed systems, microservices, and API-driven architectures.
Strong understanding of distributed systems principles, including consistency, availability, durability, reliability, fault tolerance, scalability, and consensus concepts.
Hands-on experience with Kubernetes, AWS or another public cloud, Docker, infrastructure-as-code tools such as Terraform or CloudFormation, and modern CI/CD practices.
Experience designing, developing, and operating microservices, cloud-native services, automation frameworks, and production-grade platform components.
Strong knowledge of algorithms, data structures, performance optimization, concurrency, and system-level tradeoffs.
Experience building or integrating data platforms, machine learning platforms, or large-scale data processing systems.
Demonstrated ability to embrace AI, apply AI-assisted engineering practices, and use data-driven insights to improve productivity, innovation, and continuous improvement.
Excellent technical communication skills, with the ability to explain complex ideas clearly, influence through technical merit, and align stakeholders across teams.
Proven ability to mentor engineers, lead technical direction, promote engineering excellence, and operate with humility, ownership, and a team-first mindset.

Nice To Haves

Experience with Large Language Models, Retrieval-Augmented Generation, vector databases, AI agents, agentic workflows, or Model Context Protocol.
Proficiency in additional languages such as JavaScript, TypeScript, Python, or Go, with a willingness to learn and adapt across technology stacks.
Experience building SaaS, PaaS, or developer platforms on AWS, GCP, or Azure.
Experience with TeamCity-based CI/CD pipelines, Argo Workflows, event-driven architecture, or Kafka-based systems on public cloud.

Responsibilities

Provide technical leadership and mentorship across multiple engineering teams, fostering a collaborative, innovative, and customer-centric engineering culture.
Design, build, and operate scalable, secure, multi-tenant, cloud-native SaaS services and platform components.
Develop microservices, APIs, automation tools, and lifecycle management capabilities for highly available distributed applications and services.
Build and operate platform capabilities using modern cloud and data technologies such as AWS, Kubernetes, Docker, Terraform, and Kafka.
Drive the adoption of AI, agentic coding tools, GenAI capabilities, and advanced automation to accelerate engineering productivity and platform innovation.
Collaborate cross-functionally with product, architecture, security, operations, and solution teams to launch new capabilities aligned with Guidewire’s AI, cloud, and platform priorities.
Own technical design, implementation quality, CI/CD pipelines, scalability, availability, observability, service reliability, and data security.
Champion proactive security, compliance, operational excellence, and reliability improvements across services and platforms.
Lead complex technical initiatives from concept through delivery, including design reviews, implementation guidance, risk management, and production readiness.
Support the growth of engineers through coaching, feedback, technical guidance, pair programming, and development opportunities.