Top Hybrid Software Engineer Jobs in Boston, MA

Own the architecture and technical direction of WHOOP’s Android connectivity layer, including BLE transport, history synchronization, firmware delivery, reliability, telemetry, and modular codebases. Collaborate with hardware, firmware, backend, and iOS teams; diagnose device-specific issues; improve testing and code quality; support releases and incident response; mentor engineers; and define modern Kotlin and Android engineering practices.

Design and deliver developer tooling, frameworks, reusable templates, AI-assisted development infrastructure, authentication and identity platforms, and cloud-native services. Build and operate Java and AWS systems using Spring Boot and Kubernetes, establish engineering standards and guardrails, improve reliability and performance, and lead complex technical projects. Partner across teams to drive adoption, alignment, and measurable engineering productivity outcomes.

Develop end-to-end full-stack solutions using front-end and back-end technologies, optimize existing products, and lead key Customer Hub initiatives. The engineer will make technical decisions, evaluate trade-offs, deploy reliable and tested software, mentor teammates, conduct code reviews, and drive projects in an agile environment. The role focuses on personalized ecommerce shopper experiences and expects effective, responsible use of AI in software development.

Build and improve end-to-end web and mobile product features for MedTech sales teams. Collaborate with customers, product managers, designers, and engineers; use data to optimize performance and identify enhancements; explore scalable technologies; contribute to engineering processes and culture; and mentor developing engineers. The role emphasizes full-stack development across multiple technologies and agentic AI development practices.

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.

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.

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.

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 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.