Senior Software Engineer

Liberty Mutual Insurance•Boston, MA

6d•$106,000 - $197,000•Hybrid

About The Position

At Liberty, you'll thrive in a hybrid setting that fosters in-person collaboration, innovation and growth. This approach optimizes both remote and in-person interactions, enabling you to connect and ideate with your team and deepen valuable relationships across the company, while still enjoying the flexibility of remote work for focused tasks and projects. This position follows a hybrid work model (2 days onsite) and is open to candidates located in Portsmouth, NH; Boston, MA; Plano, TX; Indianapolis, IN; and Columbus, OH. Want to work at the leading edge of emerging technology and rapidly expand your engineering skill set? Join Best Coding Squad (BCS), where we develop full-stack solutions with a strong focus on data and insights. Our applications feature cutting-edge GenAI capabilities, agentic workflows, and embedded predictive models (pricing, risk selection, desirability, and more) that streamline manual processes and improve decision-making for our users. As part of BCS, you'll join a cross-functional team of Data Scientists, Data Engineers, and Software Engineers, working together to design data-centric solutions for our business stakeholders. Together, we build, test, and maintain the technical architecture behind our applications, data pipelines, databases, APIs, and predictive model workflows. The ideal candidate is a strong communicator with excellent self-motivation and a proactive approach to learning. A growth mindset is essential as we're constantly exploring new and emerging technologies at the frontier of AI.

Requirements

A minimum of five years of software engineering experience
A Bachelor’s or Master’s degree in a technical or business discipline, or equivalent experience
Generally 4-6+ years of professional experience
Strong oral and written communication skills; presentation skills
Proficient in consensus building and facilitation
Ability to learn and adopt new technologies
Understanding of AWS architectures and technical standards
Proficiency in multiple programming languages and tools
Understanding of agile data engineering concepts and processes
Consultative skills, including the ability to understand and apply customer requirements, drawing out unforeseen implications and making recommendations for design, the ability to define design reasoning, and understanding potential impacts of design requirements
Collaboration, prioritization, and adaptability skills required
Python, TypeScript/Node.js
React
SQL and relational database concepts, Postgres / pgvector
Microservices, REST APIs, JSON, Postman
GitHub Actions (preferable) or equivalent experience such as Bamboo, Jenkins, or Azure DevOps
AWS: CDK, Glue, Lambdas, S3, Step Functions, DynamoDB, ECS, Fargate, SQS, API Gateway, AgentCore
Observability: DataDog, MLflow 3
GenAI: Experience with LLM orchestration, search systems, and context engineering

Nice To Haves

API development: Experience building and scaling APIs for both high-throughput and low-latency applications. Should be able to communicate architectural trade-offs when designing complex API systems.
LLM expertise: Hands-on experience invoking LLMs and running prompt experiments, plus the ability to articulate how LLM invocation patterns are treated in API design
Agent workflows: Experience building agents with established frameworks such as LangChain, LangGraph, or CrewAI
Search systems and context engineering: Experience with RAG, semantic search, vector stores, and knowledge graphs
Experience with workflow observability, including prompt and model tracking tools (MLflow, LangSmith, or equivalent)

Responsibilities

Design and develop technical solutions as part of an agile team
Work in a dynamic and exciting agile environment with Scrum Masters, Product Managers, and team members to develop creative data-driven solutions that meet business and technical initiatives
Work directly with data scientists to provision data for model development and AI workflows
Interact with internal stakeholders and the core development team to refine the product backlog
Automate and execute all levels of testing (unit, integration, and regression)
Design and develop solutions to support ingestion, curation, and provisioning of complex enterprise data to achieve analytics, reporting, and data science
Support custom applications through their entire lifecycle
Proactively avoid and eliminate technical debt
Champion engineering excellence
Foster a learning/growth mindset and model it for others