Senior Software Engineer
Description
Do you have the skills - and drive - to join a tech team that’s working to digitally transform a trillion-dollar industry? From test-driving the latest technologies to creating intuitive consumer apps, Liberty Mutual is constantly innovating and creating industry-leading solutions that provide peace of mind for our customers worldwide. As a senior software engineer at Liberty Mutual, you’ll apply your talents in an agile environment that has the creative energy of a start-up - and the full backing and comprehensive benefits of a Fortune 100 company.
Hiring Manager: Kevin Mayer, USRM Claims Tech
About the team
You’ll join The Auto Physical Damage (APD) squad within Liberty Mutual’s Claims Predictive Modeling domain. Our engineers are the bridge between data science and production: we partner directly with data scientists to take predictive and generative AI models out of the lab and operationalize them as real-time and batch services that drive automated claims decisions.
Who you’ll work with
You’ll sit on a scrum squad alongside product owners, a solutions engineer, and fellow engineers - and you’ll work shoulder-to-shoulder with the claims data science team. Data science owns model development and prompt engineering; Our team owns the deployed environments, the integration architecture, and the production health of everything that ships. You’ll also partner with the teams that consume our output, including the adjuster-facing claims platforms and downstream subrogation and intake systems.
Responsibilities
- Model operationalization: Partner with data scientists to deploy models as production microservices, building the feature pipelines, orchestration, and integration layers that deliver predictions to downstream claims systems
- Integration engineering: Build and maintain event-driven and API-based integrations between predictive services and enterprise claims platforms, including Guidewire Navigator and FNOL intake
- GenAI enablement: Help operationalize generative AI use cases in the claims space - including prompt-driven services and the evaluation frameworks that measure whether LLM output is good enough to act on
- Production ownership: Own monitoring, alerting, and operational support for the services the squad runs, including on-call and service desk support for live model integrations
- Collaborative partner: Working with our team of scrum masters, product owners and fellow engineers, you’ll tackle technical challenges and ensure quality as we move from legacy technologies to next-generation applications
- Comprehensive problem-solver: As you manage the end-to-end development of software products, you’ll analyze issues at the system level and handle any complications that arise by implementing effective solutions
- Skilled technical engineer: You’ll document and lead the implementation of technical features, improvements and innovations
- Forward thinker: Simply fixing the problem isn’t enough; using your proactive mindset and initiative, you’ll continually look for ways to improve performance, quality and efficiency
Qualifications
- A minimum of five years of software engineering experience
- Hands-on experience with Java and Spring Boot for microservice development
- Experience building on AWS - Lambda, API Gateway, Step Functions, SQS, DynamoDB, S3, and RDS/MySQL - ideally with infrastructure as code (AWS CDK)
- Python for CDK
- Experience with event-driven and data pipeline technologies such as Kafka, Apache Airflow, and Snowflake
- Familiarity with MLOps concepts - model deployment, versioning, feature pipelines, and monitoring of model-serving services
- Experience with observability tooling (Datadog, Splunk) and CI/CD pipelines
- A history of translating client requirements into technical designs
- Agile engineering capabilities and a design-thinking mindset
- Collaboration, adaptability, flexibility and the ability to manage time and prioritize work with a globally distributed development team
- Strong oral and written communication skills - and a knack for explaining your decision-making process to non-engineers
- A thorough grasp of IT concepts, business operations, design and development tools, system architecture and technical standards, shared software concepts and layered solutions and designs
- An understanding of how modifications affect different parts of a system
- A background in business operations and strategies, with a focus on business IT
- A bachelor’s or master’s degree in a technical or business discipline, or equivalent experience
Nice to have, but not required
- Exposure to LLM/GenAI application patterns - prompt engineering, retrieval, evaluation and quality metrics
- Insurance claims domain knowledge
- Databricks platform
- Experience with computer vision or OCR pipelines