Top Senior Level Jobs in Boston, MA

Own global, full-cycle talent acquisition with a primary focus on enterprise sales and GTM hiring. Build proactive talent pipelines, partner with senior leaders and hiring managers, manage recruiting in Greenhouse, improve interview processes, deliver strong candidate experiences, and use funnel metrics and hiring data to improve outcomes. The role also supports TA projects, process optimization, interviewer coaching, and broader hiring needs in a hybrid Boston environment.

Build and operate production AI-enabled healthcare products end to end, including backend services, data pipelines, EHR integrations, AI agents, evaluation systems, cloud infrastructure, and user interfaces. Own deployment, observability, security, reliability, and technical architecture for systems used by patients and care teams. Partner with product, clinical, design, operations, legal, privacy, and engineering teams while establishing development, evaluation, documentation, and operational standards.

Lead MacPaw’s global PR and communications strategy, shape corporate and product narratives, build relationships with top-tier technology media, manage reputation and industry events, establish PR KPIs and reporting, integrate AI into communications workflows, oversee budgets, and mentor a high-performing PR team.

Field-based Account Executive responsible for hunting and closing institutional B2B nursing education sales within New England. Generate pipeline via cold outreach, demos, events, and webinars (60–70%); manage onboarding, retention, and upsell activities (30–40%). Meet quotas, maintain CRM data, collaborate cross-functionally, and travel extensively to secure bulk institutional contracts.

Lead the Cloud Platform engineering team responsible for scaling and operating nRF Cloud, an IoT platform supporting millions of devices. Own reliability, performance, infrastructure, databases, security, observability, and the technical roadmap. Manage team productivity, culture, hiring, and cross-functional alignment while remaining hands-on through architecture, code reviews, and production debugging. Drive platform excellence, sustainable on-call practices, and pragmatic technical investment.

Lead enterprise AI engineering strategy and teams building scalable agentic AI platforms. Oversee foundation model training, LLM inference, similarity search, guardrails, evaluation, governance, observability, and AI operations. Drive build-versus-buy decisions, optimization, responsible AI practices, multi-year technical roadmaps, and cross-functional alignment while developing senior engineering talent and supporting hundreds of production use cases.

Lead Amazon performance marketing strategy and execution, manage Sponsored Ads and DSP, collaborate with agencies and cross-functional teams, optimize campaigns and budgets, analyze performance with AMC/analytics, and measure commercial impact to drive ROAS and customer acquisition.

Own technical post-sale relationships for enterprise customers, driving onboarding, adoption, optimization, integration, consumption growth, renewals, and upsell opportunities. Serve as the customer’s technical advocate with product and engineering teams, solve technical issues, maintain project documentation, and guide customers in using New Relic’s observability platform. This field-based role requires some travel and strong technical, business, and customer-facing skills.

Lead security across data, cloud, applications, corporate systems, and AI platforms. Manage incident response, security monitoring, vulnerability management, automation, governance, regulated-data controls, vendor relationships, budget, and the security roadmap. Build and manage a security engineering team, partner with engineering and infrastructure teams, conduct control testing and tabletop exercises, support audit readiness, and report security posture and risks to leadership.

Build and maintain production forecasting models for recognized revenue and COGS, connecting product usage, pricing, infrastructure costs, and unit economics. Partner with Finance, Product, Engineering, Data Science, and Go-to-Market teams on planning, scenario analysis, variance investigations, and model governance. Establish forecasting standards, monitor accuracy and drift, develop scalable data foundations, and communicate insights to technical stakeholders and executives.