Top Hybrid Software Engineer Jobs in Boston, MA

Build and maintain full-stack features supporting member acquisition, onboarding, engagement, and retention. Develop frontend applications with modern web technologies, optimize APIs and infrastructure for e-commerce and growth experiments, troubleshoot production issues, improve reliability, participate in code reviews, and collaborate with product, design, and engineering teams in an iterative environment.

Build backend systems for ingesting, processing, and exposing health record data from EHRs and third-party platforms. Develop secure APIs, scalable data pipelines, and services that normalize and validate sensitive healthcare data. Collaborate with product, data science, and engineering teams, while contributing to code reviews, testing, documentation, privacy, security, and access control practices.

Leads and manages a software engineering team focused on growth initiatives including member acquisition, retention, revenue generation, experimentation, referrals, and global expansion. Defines technical strategy and architecture, collaborates with product, design, finance, and marketing, and ensures strong development, testing, and deployment practices. Provides mentorship, performance feedback, and coaching while fostering innovation, psychological safety, teamwork, and continuous learning.

Leads software engineering projects and developer teams building distributed microservices and cloud-based backend solutions. Collaborates with product managers, mentors engineers, evaluates code, and addresses regulatory and customer needs. Uses technologies including Java, Python, Go, Node.js, SQL, AWS, Docker, Kubernetes, relational databases, and NoSQL databases while staying current with emerging technologies and AI tooling.

Owns resilience, performance, scalability, and operational cost improvements for a cloud-native platform. Designs and delivers full-stack solutions, builds monitoring and analysis capabilities, performs architectural and code reviews, and resolves complex production issues. The role requires pragmatic modernization judgment, AI-assisted development experience, customer or user accountability, and participation in a weekend on-call rotation.

Leads multiple engineering teams, owning software delivery, SDLC quality, people management, strategic alignment, resource planning, incident governance, and team development. Partners with Product and business stakeholders on prioritization, estimation, communication, execution, and performance metrics. The role requires experience with large-scale, low-latency distributed systems, agile delivery, DevOps, CI/CD, automated testing, infrastructure as code, distributed teams, and scalable data technologies.

Designs, develops, integrates, tests, and supports scalable data integration solutions for Liberty Mutual’s OneGL finance ecosystem. Leads improvements to data pipeline performance, scalability, maintainability, availability, and resilience. Responsibilities include data analysis, defect investigation, test scripting, architecture documentation, requirements and solution design, implementation support, cutover planning, production troubleshooting, and collaboration with technical and business stakeholders supporting the financial month-end close process.

Leads Agent Assist, Workflow, and Tooling engineering teams; sets technical strategy; architects scalable customer-care systems; delivers AI/ML solutions; oversees modernization, DevOps, security, reliability, roadmap planning, and cross-functional execution. Builds and mentors engineering managers and senior engineers while driving operational excellence and improved customer and agent experiences.

Build and deploy AI-native tools, agents, automations, and integrations supporting go-to-market teams. Develop LLM-powered workflows for CRM enrichment, account scoring, deal intelligence, and outreach. Partner with Sales, Marketing, Customer Success, Revenue Operations, Finance, Product, Engineering, and Data teams to define measurable solutions. Own projects end to end, including prototyping, backend services, deployment, monitoring, evaluation, data-quality guardrails, adoption measurement, and continuous improvement across the GTM technology ecosystem.

Build developer-experience tooling and frameworks for efficient development, testing, packaging, and rapid production releases. Lead release tooling design, establish quality feedback loops, improve engineering workflows through qualitative and quantitative feedback, and promote effective engineering practices. Collaborate with product managers, designers, and engineers to enhance developer productivity and satisfaction while contributing to team and process growth.

Build and maintain scalable backend systems and APIs for high-volume, real-time sports betting applications. Own the full software development lifecycle, deliver production-ready features, resolve production issues, optimize performance and reliability, collaborate with product and engineering teams, and mentor peers. Requires backend development experience with C# or Java, cloud-based distributed systems expertise, automated testing proficiency, and strong object-oriented design knowledge.

Designs and implements scalable data processing, analytics, machine learning, ETL, and cloud-native workflows. Builds data ingestion pipelines, infrastructure, data models, dashboards, and machine learning deployments using AWS services. Ensures data quality, integrity, and operational performance through monitoring and troubleshooting. Collaborates with data scientists, analysts, product managers, and engineers to gather requirements, manage backlogs, document processes, and deliver reliable solutions using Agile practices.