Top Hybrid Software Engineer Jobs in Boston, MA

Develop software solutions for Assurance client engagements, participating in architecture, design, coding, testing, maintenance, and code reviews. Collaborate with project teams to create scalable systems, apply computer science and engineering principles, interpret data, and provide technical insights. The role emphasizes learning, innovation, client service, teamwork, adaptability, and using AI and emerging technologies to improve financial reporting and decision-making processes.

Leads engineering teams developing automation and robotic process automation solutions while advancing responsible AI-enabled transformation. Partners with product, operations, and technology leaders to modernize service processes, reduce manual effort, improve quality, and deliver employee and customer value. Responsibilities include managing complex technology development, optimizing teams, applying technology standards, building cross-functional consensus, and translating emerging technologies into practical business solutions.

Build and operate production software for active clinical trials, including clinical-system integrations, trial data flows, site activation, monitoring, and signal detection. Design AI-native agents and pipelines with auditability, provenance tracking, and human review in regulated GxP environments. Own multi-quarter technical initiatives, collaborate with clinical, regulatory, QA, data, and infrastructure teams, mentor engineers, and improve validated software delivery workflows.

Develop scalable customer-facing features and internal developer-experience tools for Chewy’s e-commerce platform. Responsibilities include system architecture, automation, observability, CI/CD, monitoring, testing, code reviews, agile collaboration, mentoring junior engineers, and production troubleshooting through on-call rotations.

Lead the architecture and evolution of AI-enabled, cloud-native software platforms. Evaluate emerging AI, machine learning, cloud, and architecture technologies; define scalable reference architectures; guide data, model integration, monitoring, security, governance, and responsible AI practices; communicate technical strategies; review implementations; and mentor engineering and architecture teams on modern development and AI-assisted engineering.

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.

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.

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.