Top Remote Jobs in Provo, UT

Design, build, and optimize agentic AI solutions, including LLM prompts, agent workflows, MCP tools, tool-calling frameworks, RAG systems, and context orchestration. Develop evaluation methods, integrate enterprise systems and APIs, support deployment and monitoring, and ensure solutions meet security, governance, compliance, and responsible AI standards. The role is client-facing and involves collaboration across product, architecture, and engineering teams.

Leads client-facing, hands-on AI engineering and solutioning from pre-sales through early delivery. Designs and implements enterprise AI platforms, agentic solutions, cloud transformations, AIOps, observability, and production AI/ML environments. Partners with enterprise architecture, operations, security, and delivery teams while supporting mission-critical and regulated platforms. Requires deep experience across AI stacks, cloud and platform engineering, enterprise architecture, stakeholder management, and transformation programs.

Build and deploy enterprise GenAI and agentic AI solutions for Fortune 2000 clients. Lead executive discovery, identify high-value use cases, rapidly engineer proofs of value, design scalable agentic architectures, and hand solutions to delivery teams. Integrate AI systems with enterprise applications and hyperscalers while addressing security, governance, evaluation, observability, and cost. Support technical sales through workshops, demos, solution architecture, and reusable accelerators.

Build and polish complex interactive video-editing features for Studio, including transitions, color grading, element libraries, presets, and customizable keyboard shortcuts. Own frontend-leaning full-stack work from proposal through launch, collaborate in a fast-moving startup environment, and contribute to product decisions and marketing efforts. Deep backend expertise is not required.

Own a greenfield workflow for distributing Studio video projects across languages and aspect ratios. Design complex data-heavy backend systems, define requirements through RFCs, pressure-test data structures, and lead projects from inception through launch with minimal supervision. The role requires product judgment, enterprise-grade usage and account reporting expertise, and backend generalist capabilities. Media or video-processing pipeline experience is a bonus.

Build and operate infrastructure supporting AI model training, inference, and product platforms. Responsibilities include managing Kubernetes and GPU clusters across cloud and on-premises environments, provisioning compute and networking, operating databases and Kafka, developing Python-based automation and self-service tooling, and leading cloud migrations and platform improvements focused on reliability, security, and cost efficiency.

Senior subject-matter expert in advertising effectiveness and creative development who advises customers and internal teams, drives go-to-market readiness, builds external thought leadership, and translates customer needs into product and GTM strategy to improve ad testing, campaign performance, and creative decisioning.

Design, build, and scale Shepherd’s core platform, backend systems, APIs, user-facing applications, and AI-powered legal workflows. Architect secure, reliable infrastructure for sensitive legal data, collaborate with legal and product teams, build internal tools, optimize performance, and own technical decisions. The role also involves rapid prototyping, mentoring and recruiting engineers, and contributing to SOC 2 readiness and data privacy practices.

Conducts insurance premium audits by scheduling client interactions, collecting and reviewing documentation, preparing accurate audit reports, and communicating with insureds and internal stakeholders. The role requires independent remote work, workload management, deadline adherence, and compliance with client and company standards.

Develops Power BI dashboards, SSRS reports, data models, KPIs, and healthcare analytics solutions. Uses advanced SQL and Python to transform, analyze, and optimize large healthcare datasets. Performs exploratory analysis, ensures data quality and governance, supports reporting and production issues, and communicates insights to technical, business, client, and executive stakeholders. Collaborates across Product, Engineering, Client Services, and Operations teams in Agile delivery environments.

Lead end-to-end design, development, and delivery of full‑stack features; drive architecture and code reviews; coordinate engineering work, write design docs and tests, and participate in Agile ceremonies. Must have blockchain/crypto experience.

Full-stack product engineer (backend-focused) who builds scalable NodeJS services, crafts React/TypeScript UIs, designs APIs, writes well-tested code, optimizes PostgreSQL queries and data pipelines, improves observability, and contributes to architecture and engineering practices for a fintech platform.

Own end-to-end product experiences for a data-intensive, AI-native fintech OS: convert complex financial logic and APIs into intuitive flows, design dashboards and workflows, build and maintain a scalable Figma design system aligned with React components, prototype with real data, and collaborate closely with engineers to ensure usable, accurate UX.

Conduct approximately 100 daily cold calls and manage replies from automated email and LinkedIn campaigns. Qualify B2B prospects, book 50 qualified meetings monthly after ramp-up, maintain accurate HubSpot records, provide detailed handoffs to Sales Executives, and use meeting feedback to improve targeting, messaging, and qualification.

Owns business value consulting for strategic commercial and enterprise SaaS accounts. Builds ROI models, financial business cases, value realization dashboards, and executive presentations supporting new sales, retention, and expansion. Partners with Sales, Customer Success, Professional Services, Product, and Marketing to measure customer outcomes, coach go-to-market teams, develop scalable value frameworks, and inform product strategy.

Lead the architecture and delivery of production-grade AI/ML systems for client engagements. Design agentic AI, LLM, RAG, search, recommendation, and classical machine learning solutions; advise client stakeholders; mentor engineering teams; oversee technical strategy, project delivery, deployment, monitoring, and iteration across AWS and GCP environments.