Top Artificial Intelligence Jobs

Lead applied research and technical direction for agent memory in production AI: define roadmap, design and build memory and retrieval architectures, run large-scale experiments, develop evaluation frameworks, and partner cross-functionally to ship reliable, personalized long-running agent capabilities.

Lead applied research and engineering for feedback-driven agentic AI: define reward modeling and reinforcement learning roadmap, design production learning loops and evaluation frameworks, run large-scale experiments, and ship research into production while partnering across product and engineering.

The role involves architecting strategic alliances, navigating partner organizations, translating cloud trends into partnership strategies, and fostering collaboration between teams to execute partnership milestones.

The role involves optimizing sourcing and procurement processes, providing strategic guidance, managing projects, and enhancing operational efficiency for clients. Responsibilities include data interpretation, supplier relationship management, and team oversight.

Lead deal-diligence analytics for private equity and corporate clients, translating complex and third-party data into actionable insights across the deal lifecycle. Oversee multiple projects, drive business development, mentor teams, improve post-deal performance, and develop data integration, visualization, and quality solutions using tools like Alteryx, Power BI, and Tableau.

Lead AI agent build and DevOps workstreams within a Data & Analytics practice. Develop and implement BI and cloud analytics solutions, build visualizations (QlikView, Spotfire), validate data integrity, manage client relationships, identify optimization opportunities, and mentor teams to ensure project delivery and performance.

Join the Topics Core Platform team to build text analytics features using LLMs and agentic systems. Work across the full stack (backend to UI), write well-tested code, participate in code reviews, collaborate with PM/UX/QE teams, and own feature delivery while learning modern AI tooling and the product tech stack.

Lead early-stage product incubation: run structured discovery, customer interviews, market analysis, and fast experiments to validate or kill concepts. Collaborate with a small pod (design, engineering, data), define stage-specific success criteria, synthesize signals into clear recommendations, and present findings to leadership. Move quickly, prioritize learning over polished deliverables, and de-risk new business ideas.

The Regional Marketing Manager at Skillsoft will develop and execute marketing strategies to drive demand and revenue growth in North America, managing campaigns, events, and stakeholder collaboration.

Lead regional field marketing across North America by developing strategy, executing multi-channel campaigns (events, webinars, ABM, digital), enabling sales, managing events, tracking performance, and collaborating cross-functionally to drive pipeline, customer engagement, and brand awareness.

Lead strategic, outcome-focused customer success engagements for enterprise clients. Advise executives on skills-based workforce transformation, drive data-led insights, champion platform adoption (including AI capabilities), coordinate cross-functional teams, and identify commercial growth opportunities while managing change and customer enablement.

Six-week hybrid/remote internship supporting Infrastructure Security. Learn cloud and infrastructure security practices, assist with vulnerability management, tooling, documentation, detection and remediation workflows, shadow engineers during reviews and incidents, complete a guided project, and present findings at internship end.

The Technical Customer Support Representative assists eCommerce merchants by providing technical support via phone, email, and chat, troubleshooting issues, and enhancing customer satisfaction through effective problem-solving and communication.

The Senior Director will design and govern the enterprise-wide data architecture, lead the analytics team, and ensure data reliability for scalable decision-making across various functions.

Lead planning and delivery of complex digital projects for EHS systems, data, and reporting. Manage cross-functional teams, own enterprise EHS system architecture and datasets, lead analytics and dashboards (Power BI, SharePoint), run full lifecycle delivery (UAT, rollout, training), ensure governance, data validation, and regulatory compliance support.

The Engineering Transformation Manager leads teams to ensure data quality and integrates automated quality solutions, collaborating with various engineering and product teams.

Design, develop, test, and maintain scalable enterprise and cloud-native software (APIs, microservices, backend services). Troubleshoot performance and integration issues, participate in architecture and code reviews, automate CI/CD pipelines, collaborate with cross-functional teams, and mentor junior engineers while applying best practices in software engineering and testing.

Sell Nexthink's Digital Employee Experience (DEX) platform into large enterprise IT organizations across the Northeast. Build territory plans, prospect and qualify pipeline, lead complex multi-stakeholder sales cycles (discovery, business case, POC, negotiation, close), and drive quota attainment while partnering with BD, marketing, solutions, channel, and services teams to enable long-term customer success and expansion.

Sell Nexthink's Digital Employee Experience platform to IT and Digital Workplace leaders. Prospect and qualify accounts, build pipeline, run discovery, coordinate internal resources, negotiate contracts, manage forecasts, and close deals while driving measurable business value.

Sell Nexthink’s Digital Employee Experience platform to mid-market enterprises (5,000–10,000 endpoints). Prospect, qualify, and build pipeline; run discovery with IT stakeholders; coordinate pre-sales, services, and partners; lead negotiations and contract management; manage forecasts and close tactical and strategic deals while acting as a trusted advisor.

Provide technical leadership to sales for enterprise Healthcare accounts in NYC: architect and demonstrate Rubrik solutions, lead POCs/demos, qualify opportunities, and act as a trusted technical advisor to customers and account teams to drive pipeline and close deals.

The Staff Site Reliability Engineer will lead reliability efforts across distributed cloud systems, focusing on architecture, automation, incident management, and team leadership, ensuring operational excellence in SaaS environments.

The Staff IT Product Manager will oversee Sales systems, ensuring SOX compliance, managing integration with Marketing technologies, and optimizing business processes for Sales and Finance operations.

Lead global music partnership operations including rights landscape, content ingestion (DDEX), metadata and publishing clearance, compliance reporting, third‑party vendor management, CMS architecture, automation of workflows, resolving complex partner issues, and cross-functional coordination with Product, Engineering, Finance, and Legal to support music-based features.

Lead product-focused quantitative analysis and machine learning projects to deliver actionable insights, metrics, and optimizations. Collaborate with product, engineering, and design teams to build scalable, statistically rigorous solutions, dashboards, and experiments. Use AI tools and high-velocity workflows to accelerate decision-making while ensuring methodological integrity and data quality.

Build and maintain People-team backend services and automations: design scalable solutions, integrate AI/LLM APIs, create middleware and chatbot integrations (Slack, Workday, Jira), automate HR workflows, deploy cloud services, and mentor junior engineers while ensuring operational excellence and testing.

The Product Marketing Lead will develop and execute marketing strategies, oversee product messaging, collaborate with teams, and drive demand generation campaigns.

The Sr. Machine Learning Engineer will develop and deploy ML solutions for healthcare, manage data pipelines, and work with large datasets to enhance healthcare delivery.