Top Engineering Jobs in Boston, MA

Leads multiple engineering teams building internal platforms, web applications, AI-powered workflows, integrations, data pipelines, and automation. Sets technical direction, oversees architecture and delivery, partners with product and business stakeholders, and develops engineering talent. The role emphasizes front-end development with TypeScript and React, CMS integrations, internationalization and localization, scalable SaaS systems, AI-enabled marketing workflows, and operational productivity improvements.

Owns the enterprise architecture of Klaviyo’s marketing technology ecosystem, integrating HubSpot, Salesforce, NetSuite, Coupa, and internal systems. Designs AI-powered marketing capabilities including generative AI, predictive scoring, intent automation, personalization, and customer journey orchestration. Builds a centralized marketing hub spanning budgeting, planning, campaign execution, performance insights, and ROI measurement. Advises cross-functional teams on technical design, integrations, governance, vendor evaluation, and scalable architecture.

Build and maintain integration and end-to-end testing frameworks across backend and frontend systems. Optimize CI/CD test execution, establish repository testing standards, develop mocking and service-isolation tools, and improve test coverage. Explore AI-driven test generation, regression detection, and flaky-test analysis. Partner with engineering teams to troubleshoot failures, monitor test-suite and pipeline health, and deliver scalable quality improvements.

Owns end-to-end architecture for Klaviyo’s marketing, sales, and customer experience systems. The role designs integrations, data models, governance, reporting, and AI-agent workflows across Salesforce and related platforms. It combines executive-level technical strategy with hands-on development using Apex, LWC, Flow, SOQL, integrations, and AI orchestration. The architect will redesign GTM processes around AI, ship production solutions, advise senior leadership, establish engineering standards, and mentor GTM Systems teammates.

Design, build, and maintain mission-critical data and analytics infrastructure on AWS. Develop high-quality code, create system infrastructure, operate distributed systems in production, and contribute to technical design. Review designs and code, establish engineering best practices, and mentor engineers across the organization. Work with large-scale data processing, storage, OLTP and OLAP databases, and real-time analytics systems.

Lead the technical vision and execution of Klaviyo’s organization-wide CI/CD platform. Responsibilities include architecting deployment and rollback pipelines, setting engineering and repository standards, building scalable developer tooling, integrating AI into testing and software delivery, advising engineering teams, conducting root-cause analysis, and ensuring platform reliability. The role requires hands-on technical leadership across backend and frontend systems, infrastructure automation, testing, and high-frequency deployments.

Design, implement, maintain, and automate enterprise IT systems spanning identity, endpoint management, SaaS platforms, integrations, and access lifecycle management. The role handles projects and technical escalations end to end, documents configurations and runbooks, measures system impact, supports security audits, and participates in after-hours on-call. It requires foundational systems administration, device management, scripting, APIs, SSO, SCIM, and AI-assisted troubleshooting skills.

Own the design, administration, reliability, security, and roadmap of enterprise identity, endpoint, and SaaS systems. Lead SSO, SCIM, device management, integrations, automation, and AI-assisted workflow projects end to end. Translate ambiguous business needs into scalable solutions, troubleshoot complex incidents, maintain audit-ready controls, evaluate vendors, document systems, mentor engineers, and participate in an after-hours on-call rotation.

Lead cross-team data platform initiatives focused on the Data Lake. Drive architecture and roadmaps for lakehouse storage, compute, orchestration, modeled data layers, and operational automation. Own large, complex programs end-to-end, make high-judgment architectural decisions, establish standards and paved paths, respond to incidents, and mentor senior engineers while aligning stakeholders across engineering, product, analytics, and AI/ML.

Design, build, and operate foundational platform services to improve availability, scalability, latency, and efficiency. Enable product teams via platform primitives (infra, databases, queuing), leverage Python, Go, AWS, Kubernetes, and Terraform, and mentor engineers to deliver resilient, scalable systems and improved developer experience.