Top Remote Jobs

Own customer support cases for Ivans digital products from initial contact through resolution. Troubleshoot configuration, data, integration, API, and potential product issues; perform root-cause analysis; guide onboarding and setup; document recurring solutions; and collaborate with Product, Engineering, and integration partners. Translate technical findings into clear customer communication and well-documented escalations.

Build and own production Vision AI systems end to end, including model selection, inference pipelines, evaluation, monitoring, and customer-facing features. Shape architecture, collaborate with product, design, and engineering teams, and use AI coding tools to accelerate development. Establish high standards for quality, testing, reliability, security, and privacy while mentoring engineers and taking ambiguous ideas from prototype to production.

Manages Chevrolet dealership relationships across West Texas, coaching dealer leadership, driving vehicle and parts sales, optimizing inventory, launching GM programs, analyzing performance, resolving concerns, and ensuring compliance with GM standards. The role requires frequent territory travel, strong business planning, data analysis, relationship management, and legal operation of a motor vehicle.

Manage and grow an installed customer base through renewals, upsells, cross-sells, and expansion opportunities. Analyze customer usage and contract data to identify whitespace, maintain accurate CRM and forecast records, negotiate renewals, and partner with Customer Success, Support, Professional Services, SDRs, and Solution Consultants. Advise clients on EDI and B2B integration best practices while using AI tools for account analysis, prioritization, outreach, conversation intelligence, and forecasting.

Build and grow strategic technology and software partnerships that generate pipeline and revenue. Identify and activate partners, develop joint go-to-market strategies, drive co-selling and referrals, establish executive relationships, coordinate with sales and technical teams, lead partner enablement and marketing programs, and manage partner performance, pipeline, business reviews, and integration adoption.

Leads DevOps and platform engineering initiatives across AWS cloud infrastructure, CI/CD, Kubernetes, Infrastructure as Code, observability, security, and SRE. Builds scalable platforms supporting consumer applications, data, machine learning, and AI workloads. Develops MLOps and AI platform capabilities, automates provisioning and operations, improves reliability and cost efficiency, and partners across engineering, data, security, and architecture teams. Provides technical leadership and mentorship while remaining a hands-on individual contributor.

Manage complex journal entries, including payroll, support monthly close, perform reconciliations and flux analysis, review accounting work, and improve financial processes and controls. Apply US GAAP to non-routine transactions while helping automate manual work and shorten the close. The role partners with corporate and technical accounting leadership in a fast-paced, remote-first environment.

Design and deliver sales training for upmarket teams, including skills workshops, roleplays, accreditation, and leadership development. Own Motive’s manager coaching framework, train frontline managers, provide practical coaching tools, and measure impact through proficiency, win rate, deal velocity, pipeline health, and accreditation outcomes. Partner with sales leaders, enablement teams, Sales Operations, and global trainers while traveling 25–45% of the time.

Leads regional candidate experience operations, including interview coordination, offers, contracts, background checks, onboarding handoffs, workload balancing, escalations, and specialist development. Builds candidate experience reporting, identifies process risks and bottlenecks, standardizes global coordination processes, and partners with recruiting, hiring managers, People Operations, IT, and talent leadership across time zones.

Designs, builds, and operates shared machine learning infrastructure, including feature stores, model hosting, inference, training, evaluation, and rules engines. Leads large-scale distributed systems, reliability improvements, incident response, and safe deployments. Partners with applied ML teams to develop reusable platform capabilities, supports internal users, mentors engineers, and contributes to technical roadmaps and design reviews.