Top Tech Jobs & Startup Jobs in Boston, MA

The Software Development Engineer in Test will design and maintain an automated testing framework for AI systems, ensuring reliability and performance through extensive testing, debugging, and collaboration with system engineers.

The Chief Financial Officer will lead global accounting and finance, drive financial strategy, oversee M&A activities and ensure operational excellence across subsidiaries.

The Project Manager is responsible for delivering key client projects on time, within budget and scope, ensuring high levels of customer satisfaction while managing project phases and progress.

Lead strategy and execution for PlanHub’s pre-construction products while collaborating with engineering and design to drive customer-centered solutions using AI.

Own the full enterprise sales cycle for RightAnswers, generate qualified pipeline via outbound/ABM/SDR collaboration, lead consultative discovery with Ops/CX/IT, build TCO/ROI value cases, run demos/POCs, coordinate cross‑functional teams and partners, close new logos and expand accounts, and feedback customer insights to Product and Marketing.

Sales Specialists will sell Cloud SaaS solutions, prepare presentations, analyze client needs, negotiate pricing, and coordinate with implementation teams for onboarding.

The Turbo Machinery Advisor will guide turbine and expander development, mentor engineers, oversee testing, and ensure regulatory compliance while leveraging industry expertise and partnerships.

As a Climate Strategist, you will develop and implement decarbonization goals for enterprise customers, collaborating with internal teams to refine value propositions and ensure customer satisfaction in a dynamic market.

The Outside Salesperson is responsible for acquiring new members by targeting Fortune 500 companies, utilizing strategic sales plans, building relationships, and negotiating large sales agreements, all while reporting performance metrics to leadership.

The role involves owning and evolving production ML systems, developing models, collaborating with stakeholders, and ensuring efficient system performance through coding and infrastructure contributions.