Top Artificial Intelligence Jobs

Reviews and evaluates domain-specific documents, providing structured feedback on quality, accuracy, and relevance. The role requires strong analytical and written communication skills, detailed document review, proficiency with spreadsheet and presentation software, and the ability to follow structured guidelines. Candidates must have a bachelor’s degree, at least three years of relevant professional experience, English proficiency, and reside in the United States, Europe, the United Kingdom, or Canada.

Generate and qualify enterprise and mid-market leads across global markets, with emphasis on the UK and US. Conduct disciplined outbound outreach through calls, email, and LinkedIn; nurture prospects; qualify opportunities using BANT; schedule sales meetings and demos; collaborate with account executives; and manage prospect data in Salesforce and related tools. Meet monthly qualified-lead targets and contribute to pipeline and closed-won growth.

Own FDNA’s growth marketing function across SEO, AI answer visibility, paid acquisition, parenting communities, social media, and influencer partnerships. Manage Google Ads, content strategy, privacy-safe tracking, funnel measurement, contractors, and clinical/legal review. Build credible, compliant campaigns for parents and clinicians while optimizing acquisition quality and product engagement.

Conduct high-volume outbound calls to real estate prospects, including owners, buyers, sellers, investors, landlords, and tenants. Qualify leads using structured discovery questions, identify motivations and timelines, schedule callbacks, generate qualified opportunities, and transfer them to representatives. Maintain accurate CRM records, dispositions, notes, and follow-ups while complying with telemarketing, privacy, and do-not-contact requirements. Performance is measured through call volume, lead quality, conversion, quality assurance, CRM accuracy, attendance, and schedule adherence.

Configure Manhattan Active Warehouse Management, develop REST and event-driven integrations, create data mappings and cloud-native extensions, and support API testing, SIT, UAT, and production troubleshooting. The role integrates MAWM with ERP, OMS, and material handling systems while collaborating with architects and functional teams in an Agile offshore engineering environment.

Own and accelerate ELSA’s B2B Dashboard during a three-month contract. Build production-ready full-stack features across Go, Python, and Vue.js; shape product requirements; make UI/UX decisions; improve APIs and user experiences; use AI development tools; and collaborate with product, design, business, and engineering stakeholders to deliver high-impact improvements autonomously.

Lead Sidetrade Pay as a global embedded B2B payments business across enterprise, SMB, and mid-market customers. Own product vision, roadmap, monetization, pricing, payment partners, adoption, risk, compliance, revenue, and P&L performance. Build payments and product teams, embed payment experiences into Order-to-Cash workflows, expand into embedded finance, and align Engineering, Sales, Customer Success, Legal, Finance, executives, and external partners across multiple regions.

Design, develop, and deploy scalable backend systems and microservices for AI solutions. Collaborate cross-functionally to ship features, optimize application performance, resolve bottlenecks and bugs, and maintain code quality, organization, and automation. The role contributes to early-stage product development and helps shape the company’s technical direction.

Develop and integrate secure AI server platform firmware for customer systems. Responsibilities include server bring-up, peripheral communication over low-level protocols, BMC software development, Linux kernel troubleshooting, secure boot and root-of-trust implementation, and platform integration across NVIDIA, Intel, and AMD architectures. The role also provides technical customer guidance, resolves complex integration issues, and supports custom hardware, embedded systems, microcontrollers, FPGAs, and ARM-based platforms.

Develop and deploy computer vision modules and machine learning models within AI pipelines. Integrate models with data and software engineering teams, support prototypes, automate data pipelines, build internal tooling, and monitor production performance. The role also involves optimization, infrastructure and security support, staying current with computer vision advancements, and collaborating cross-functionally.