Top Senior Level Jobs in Boston, MA

Designs and owns scalable CI/CD pipelines, distributed build and test infrastructure, release automation, and engineering workflows. The role improves pipeline reliability, performance, observability, test parallelization, and release quality across multiple teams. Responsibilities include troubleshooting complex infrastructure failures, evolving branching and versioning strategies, integrating quality gates, leading technical initiatives, mentoring engineers, and applying validated AI-assisted engineering workflows.

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.

Manage strategic enterprise accounts as the primary customer contact, building executive relationships, driving product adoption, retention, and expansion. Develop account strategies, collaborate with Workday and ServiceNow partners, coordinate with Sales, Product, and Customer Success, monitor account health and usage data, and deliver executive business reviews. The role requires strong enterprise account management, consultative communication, technical acumen, strategic analysis, and stakeholder management experience in B2B SaaS, preferably HR technology.

Oversee fund accounting and securities records, resolve transaction exceptions, implement operational controls, and improve fund servicing processes. Partner with Operations, Technology, Product, Sales, and Program Management teams while identifying vulnerabilities and supporting accurate, timely administration.

Leads executive-level client partnerships, strategic account planning, complex multi-product negotiations, revenue expansion, and consultative sales initiatives. Delivers data-driven presentations and QBRs, identifies growth opportunities, collaborates cross-functionally, mentors revenue teams, and drives strategic client outcomes. Requires travel exceeding 40% and supports major advertising, retail, and consumer packaged goods accounts.

Manage technical escalations for the DV+ platform, analyze large datasets with SQL and Excel, leverage AI tools to automate workflows, troubleshoot complex integrations and APIs, and coordinate cross-functional teams to drive scalable operational solutions.

Leads measurement and product marketing for eight enterprise AI platforms. Builds shared KPI, taxonomy, scorecard, data-quality, and value-realization frameworks; translates usage and outcome data into executive insights and investment guidance. Oversees positioning, internal launches, campaigns, enablement, adoption, and audience segmentation. Partners across product, engineering, data, communications, and business teams while building and managing teams responsible for analytics, marketing, and communications.

Build and operate reliable data systems and products supporting clinical operations, drug evaluation, business development, analytics, machine learning, and AI agents. Responsibilities include designing pipelines, canonical data models, data contracts, warehouse transformations, quality and observability practices, governance for regulated data, and incident response. The role partners closely with Product Engineering and Data Science, uses AI-assisted development, contributes to architecture, and mentors other engineers.

Build and maintain platform tools, infrastructure, and automation that enable reliable software delivery at scale. Develop C# and .NET Core solutions, manage Kubernetes environments, implement Helm and GitOps deployment practices, and support distributed microservice systems. Troubleshoot complex infrastructure issues, improve observability and performance, collaborate with engineering teams, conduct code reviews, and mentor engineers.

Lead and grow WHOOP’s Analytics Engineering team while owning the quality, scalability, and evolution of its analytics transformation layer. Build reliable, documented, tested data models; translate business and analytics needs into scalable solutions; and coordinate with Data Engineering and Analytics Platform on pipelines, contracts, and architecture. Establish dbt and software-engineering standards, manage team priorities and roadmap execution, and support AI-ready analytical data and development workflows.