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# software engineer

- **Company:** Liberty Mutual Insurance
- **Location:** Boston, MA, United States
- **Experience:** Expert
- **Salary:** $140,000.0 - $155,000.0
- **Contract:** Permanent contract
- **Skills:** Java (Programming Language), Airflow, Computer Vision, Python (Programming Language), MySQL, Scaled Agile Framework, Software Engineering, Systems Architecture, Management of Software Versions, Datadog, AWS Cdk, Large Language Models, Snowflake, Prompt Engineering, Spring-boot, State Machines, AWS Lambda, Amazon Relational Database Service, Information Technology, Enterprise Integration, Apache Kafka, Machine Learning Operations, Api Design, Api Gateway, Splunk, Data Pipelines, Guidewire, Databricks, Microservices
- **Published:** September 12, 2026
- **Apply:** https://careers-libertymutual.icims.com/jobs/243161/senior-software-engineer/job?mode=apply&apply=yes&in_iframe=1&hashed=-1834448064

## About the Role

* 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

## Description

* 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


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