Top Tech Jobs & Startup Jobs in Boston, MA

Leads global thought leadership and brand authority marketing programs for academic and government audiences. Owns channel activation across owned, paid, and earned media; develops scalable frameworks, processes, and measurement approaches; aligns cross-functional stakeholders; mentors marketing leaders; and drives brand visibility, audience engagement, institutional decision-maker reach, and consistent messaging across the customer lifecycle.

Leads lifecycle marketing strategy, roadmap, web experience, KPIs, testing, and always-on programs across acquisition, adoption, expansion, and renewal. Manages a distributed marketing team, drives cross-functional alignment with product, customer success, audience, and digital operations teams, informs the marketing technology roadmap, and develops scalable programs that improve measurable commercial outcomes.

Lead the vision, roadmap, discovery, and delivery of AI-enabled analytics products for nursing and medical education. Translate customer and business needs into product strategies, prioritize backlogs, guide cross-functional teams, and measure adoption, usability, customer impact, and business outcomes. Champion responsible AI practices involving quality, privacy, transparency, and trust while using customer feedback and product data to continuously improve products.

Develop and lead strategic brand storytelling and integrated communications campaigns for Cell Press. Create and edit content, manage freelancers and agencies, coordinate web, social, and email channels, define KPIs, analyze campaign performance, and present recommendations to senior stakeholders. The role combines strategic planning, hands-on content development, project management, audience segmentation, stakeholder influence, and data-informed optimization.

Build and ship production-grade AI features, including RAG pipelines, tool-augmented agents, and agentic workflows. Integrate AI capabilities into enterprise systems, contribute to evaluation, observability, guardrails, and outcome measurement, and maintain reusable technical patterns. Collaborate with stakeholders to ensure solutions fit real workflows, identify risks, complete bug fixes, document implementations, and support handover and capability-building.

Own analytics product initiatives from discovery through launch and iteration. Define user needs, prioritize opportunities, write requirements, and collaborate with Engineering, Data Science, UX, and business teams. Use analytics and AI to improve workflows and decision-making while considering data quality, privacy, transparency, and trust. Track adoption and impact to guide ongoing product improvements.

Leads technical execution for an embedded AI innovation squad, taking prototypes from discovery through production. Designs reusable agentic AI architectures covering orchestration, tool use, memory, retrieval, integrations, security, and governance. Works with stakeholders to define requirements, makes architecture decisions, develops reference implementations, and establishes measurable outcomes. Provides infrastructure and budget recommendations, resolves complex technical issues, manages delivery dependencies, serves as the primary AI and coding expert, and mentors engineers while evaluating emerging technologies.

Build and maintain reliable, scalable platforms and services. Responsibilities include monitoring, incident response, post-mortems, disaster recovery testing, production automation, AI service deployment, infrastructure documentation, and reliability testing. The role requires advanced Terraform, AWS operations, GitHub Actions CI/CD, containerized ECS Fargate environments, networking and security expertise, Linux and scripting skills, observability, and developer enablement across engineering teams.

Manages corporate accounts to drive revenue growth, renewals, and new sales opportunities. Builds strategic customer relationships, conducts needs analyses, develops account plans, positions Elsevier’s portfolio, forecasts performance, and collaborates with marketing, product, and customer success teams. Requires consultative selling, strategic account planning, stakeholder management, and effective communication in a complex matrix environment.

As a Senior ML Ops Engineer, you will bridge Data Science and Engineering to automate ML workflows, manage CI/CD for ML systems, and collaborate with various teams to implement solutions for AI features and services.