Top Software Engineer Jobs in Boston, MA

Lead the Customer Agent AI project at Klaviyo, managing engineering teams, defining technical direction, and driving architectural decisions to develop a conversational AI platform.

Early-career front-end developer embedded in D2C; triage and fix backlog tickets, ship production code, work in agile sprints, translate design into technical requirements, use AI-assisted development to accelerate debugging and QA, and report site health and velocity to stakeholders.

Design, build, and operate the Orders API: implement new features, define testing strategy, ensure production reliability and observability, participate in architecture and code reviews, collaborate cross-functionally, and leverage AI tools to improve development velocity and platform quality.

Lead and grow multiple product-focused engineering teams to design, build, deploy, and operate scalable, highly available full-stack and microservice solutions on AWS. Mentor engineers, drive engineering practices, break monoliths into microservices, improve velocity, and collaborate with product managers to deliver finance-focused systems including event-driven streaming and integrations.

Develop scalable Java and AWS applications, customer-facing features, automation, observability, and self-service engineering solutions. Responsibilities include system architecture, prototyping, code reviews, CI/CD and infrastructure improvements, monitoring, production troubleshooting, Scrum participation, on-call support, and mentoring junior engineers.

Full-stack software engineer focusing on frontend React components and backend microservices. Design and implement scalable, resilient solutions; build/integrate RESTful APIs with Java/Spring; participate in architecture and code reviews, CI/CD, monitoring, on-call rotations, and mentor junior engineers.

Design, build, and support Java and Spring Boot event-driven microservices, REST APIs, business rules libraries, and underwriting and pricing services. Own development through testing, deployment, monitoring, incident response, and production support. Collaborate with product owners and domain experts, conduct impact analysis, troubleshoot issues, improve performance, and mentor junior engineers within an Agile team.

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.