Top Engineering Jobs in Boston, MA

Lead and manage end-to-end software engineering programs, coaching teams and coordinating cross-functional stakeholders. Oversee planning, budgeting, execution, and delivery of enterprise applications (including low-code platforms). Drive quality through ATDD, CI/CD, code review and architecture best practices (microservices/API management). Mentor staff, resolve technical and stakeholder conflicts, apply emerging AI technologies, and improve processes to meet engagement objectives and client expectations.

Provide regulatory compliance guidance and cybersecurity risk management to clients. Conduct compliance risk assessments and audits, implement frameworks (ISO/IEC 27001, NIST CSF), develop compliance programs, analyze data for insights, lead training on AML and financial crime prevention, and build client relationships while upholding professional standards.

Lead redesign of the Customer Success unified data model and AI data strategy. Build and optimize pipelines, integrations (contact center), testing/monitoring, and a documented semantic layer. Manage and mentor a small team, partner cross-functionally on KPIs, governance, and data quality, and ensure CS data is reliable for dashboards, reporting, and AI use cases.

Lead and mentor a multidisciplinary engineering team to build and deliver scalable security products (identity management, threat detection, data protection). Drive technical roadmap, manage delivery timelines and risks, enforce security best practices and operational excellence, and own recruitment, performance, and career development for the team.

Develop custom systems for hypersonic flight vehicles, manage technical requirements, and participate in collaborative engineering efforts and testing activities.

Lead and scale a multidisciplinary Platform Engineering organization owning cloud infrastructure, developer experience, SRE, and DevSecOps. Define technical strategy, run CI/CD and monorepo systems, drive AI-assisted and agentic development adoption, ensure reliability and cost-efficiency, and recruit and develop engineering leaders while partnering with product, security, and stakeholders.

Lead and manage a team delivering full-stack, cloud-based microservices solutions for risk management. Collaborate with product managers, mentor engineers, evaluate and occasionally write code, and drive adoption of modern tech (cloud, containers, databases, AI tooling) to meet regulatory and business needs.

Lead the production infrastructure organization to define platform primitives (compute, storage, networking, observability), drive reliability (SLOs/SLIs, incident management, capacity planning), create golden paths and cost-effective frameworks, mentor and scale teams, collaborate cross-functionally on platform investments, and apply AI to improve infrastructure operations and developer productivity.

Lead and grow a full-stack engineering team delivering cloud-native, microservices-based risk management solutions. Collaborate with product managers, mentor engineers, oversee architecture and delivery, and occasionally contribute code. Drive adoption of modern cloud, container, and AI/ML technologies to build scalable, compliant systems.

Lead an AI engineering team to design, build, deploy, and support foundation-model and LLM-based systems. Oversee model training, inference, similarity search, guardrails, evaluation, observability, and scalability optimizations. Make build-vs-buy decisions across OSS and SaaS AI technologies, set technical vision and roadmap, and recruit, mentor, and retain engineering talent.

Lead technical direction and development of core platform primitives (infrastructure, databases, queuing, observability). Own multi-team platform initiatives, improve scalability, availability, latency, and cost-efficiency, mentor engineers, drive on-call and reliability practices, and leverage Python/Go, cloud-native tools, and IaC to enable product teams to build and operate confidently.

Lead assessment and mitigation of AI/ML security risks across enterprise systems. Perform security reviews of AI-enabled SaaS and integrations, define AI guardrails, analyze data flows, recommend controls for data protection, and align implementations with SOX, FedRAMP, ISO 27001, and SOC 2. Partner with compliance, cloud, and identity teams to secure AI workloads and enforce logging, access, and governance.

Lead and manage a team delivering end-user device platforms and services across corporate and retail users. Own architecture, implementation, troubleshooting, and lifecycle for Windows and macOS endpoints and management tooling. Act as escalation for executive support, collaborate with vendors and partners, apply ITIL practices, drive metrics-driven improvements, and develop staff to ensure secure, available, and customer-centered end user technology.

The Mechanical Engineering Technician will oversee the machine and assembly shop, assist in prototyping parts, create fixtures, and ensure shop organization and maintenance.

The Platform Engineering Product Director will lead enterprise integration strategy and middleware platforms, focusing on scalability, performance, and integration solutions across various business functions, while mentoring teams and managing vendor relationships.

Lead the execution of mission-critical systems for aviation operations, managing multiple engineering teams, ensuring performance and compliance.

The Director of R&D Mechanical Engineering at SharkNinja will lead the engineering team, shape R&D strategy, drive innovation, and champion technical excellence across multiple product development programs.

Lead the design and implementation of integrated consumer experience solutions using Salesforce Service Cloud and CCaaS platforms, focusing on automation, AI integration, and seamless consumer journeys.

Lead and scale the IT Systems engineering organization responsible for SaaS systems, identity and access (Okta), endpoint management (Jamf/Intune), and networking. Build team structure and engineering leaders, set technical direction and standards, drive automation and operational excellence, establish scalable processes (project intake, incident and change management), manage vendors and SaaS lifecycle, and partner with cross-functional stakeholders to deliver business-aligned outcomes.

Lead and grow an AI engineering team to build internal copilots, agents, and an AI platform. Act as a player-coach contributing to architecture, prototypes, and code. Define technical roadmap, partner with business leaders to ship AI-native workflows, and ensure governance, observability, evaluation, and cost controls for LLM-driven systems.

Lead and execute SharkNinja's AI integration across the engineering lifecycle: build unified engineering data infrastructure, deploy AI-powered tooling for design, testing, reliability, and program management, embed AI Fellows into teams, drive change management and adoption, and deliver measurable outcomes tied to faster, higher-quality product development.

Lead and mature global security engineering across Application, AI/LLM, Cloud, Corporate Security, SecOps, and Red Teaming. Translate CISO strategy into secure architecture, automated risk mitigation, adversarial testing, incident response, regulatory readiness, and executive reporting while hiring, mentoring, and collaborating cross-functionally to protect global payment systems.

Lead and scale Sales Engineering teams in North America, defining strategies and collaborating with global stakeholders to drive technical sales success.

Lead design, development, and delivery of enterprise data engineering and software solutions for PwC Tax. Drive client engagements, business development, architecture and integration, mentor teams, and ensure data integrity and compliance while promoting advanced engineering practices.

Co-op supporting early-stage product development by generating user-centered concepts, building and testing rapid prototypes, running design studies and user tests, and iterating designs with cross-functional teams. Emphasis on mechanical design, ergonomics, materials, and feasibility from concept through prototyping.