Top Tech Jobs & Startup Jobs in Boston, MA

Manage day-to-day office operations for a 65-person robotics company. Responsibilities include stocking supplies, placing orders, coordinating vendors and cleaning services, liaising with landlords and property management, and organizing company events, meetings, catering, travel, and lodging. The role requires strong organization, vendor accountability, event-planning skills, clear communication, and regular onsite availability.

Design AI-powered features for Toast’s marketing website, including chatbots, conversational interfaces, and personalized visitor experiences. Translate AI capabilities into intuitive interactions, collaborate with engineering, AI/ML, marketing, and web strategy teams, prototype and test concepts, refine designs using feedback and data, and evolve design patterns for AI-enabled web experiences.

Leads PagerDuty’s Solutions Consulting function, likely overseeing customer-facing technical solution strategy for digital operations management, cloud migration, DevOps modernization, AI/ML, and automation initiatives. The provided description contains limited role-specific responsibilities or qualifications and primarily covers company information, work model, benefits, and employment policies.

Owns global alliance strategy and partner growth for ServiceNow’s Autonomous Workforce practice. The role develops joint go-to-market plans, expands partner capabilities, drives pipeline and revenue, coordinates regional execution, facilitates governance and reporting, leads enablement and demand generation, and collaborates with technical advisors and field sales. Success depends on partner maturity, global execution consistency, market expansion, revenue contribution, and executive relationship management.

Harden and maintain AWS GovCloud, Microsoft GCC High, cloud, endpoint, container, and CI/CD environments for defense applications. Investigate vulnerabilities, secure software supply chains, lead threat modeling, enforce configuration and patching policies, monitor SIEM and cloud security alerts, and support federal compliance with CMMC, NIST, and FedRAMP standards. Collaborate across product, platform, and compliance teams to integrate security into the SDLC and support incident response.

Build and maintain customer relationships to drive software renewals, retention, adoption, loyalty, upsell, and cross-sell opportunities. The specialist aligns customer goals with SmartBear solutions, facilitates onboarding and product utilization, identifies customer needs, educates customers on additional products, and provides recommendations to improve product success. The role requires strong communication, consultation, analytical, relationship-building, and customer-facing sales or account management skills.

Build and operate production-grade ELT pipelines from product, Salesforce, and third-party systems into Snowflake using dbt. Ensure testing, monitoring, schema versioning, governance, privacy, access controls, data quality, cost, and performance. Support AI initiatives with trusted data, contribute to warehouse and semantic-layer architecture, and translate cross-functional stakeholder needs into scalable data solutions.

Partners with enterprise Account Executives and sales leaders to qualify and close complex travel technology deals. Demonstrates Navan’s platform, presents value propositions to travel managers, conducts strategy sessions, scopes solutions, runs proof-of-concepts and workshops, produces business value assessments, and supports pipeline progression. The role also enables Account Executives, provides competitive insights, and shares feedback with product and operations teams while contributing to sales quota attainment.

Provides Level 2 technical support for autonomous mobile robot systems by triaging Zendesk and Jira issues, diagnosing hardware and deployment problems, coordinating with customers, site teams, and engineering, documenting resolutions, and improving troubleshooting resources. The role supports international sites and contributes feedback on recurring issues and product improvements.

Build production AI agents and agent-powered features from research and prototyping through deployment. Develop evaluation infrastructure with golden datasets, regression suites, and offline/online scoring. Own retrieval and context pipelines, production instrumentation, failure taxonomies, and cost and latency budgets. Partner with data science and product management on experiments and agent behavior, while establishing LLM engineering patterns, guardrails, and reusable tooling.