Artificial Intelligence Jobs in West Jordan, UT

Owns strategy, roadmap, and execution for KYC data intelligence products supporting financial crime risk management. Leads customer discovery, requirements, prioritization, development, launch, adoption, and optimization while partnering with engineering, data, sales, marketing, services, customers, and partners. The role requires enterprise SaaS product management expertise, technical fluency, commercial judgment, and familiarity with KYC, AML, AI, analytics, APIs, and regulated financial services.

Leads and mentors an engineering team building AI-powered features for client-facing applications. Partners with Product and UX to define roadmaps, architects AI integrations, evaluates models and vendors, and ships reliable production software. Responsibilities include hands-on coding, AI evaluation and monitoring, safety and privacy controls, telemetry, progressive rollouts, testing, and cost and latency optimization. The role also promotes responsible use of AI-assisted development tools and translates ML capabilities into customer-focused product experiences.

Leads the organization’s quality engineering discipline across AI quality, test automation, and performance engineering. The role defines AI-assisted testing strategy, architects scalable UI/API/integration frameworks, embeds testing into CI/CD, establishes performance and reliability standards, and oversees enterprise-scale load testing. It also manages multi-team engineering organizations, hires and develops senior technical talent, sets technical direction and career frameworks, and partners with Product, DevOps, R&D, and SRE leadership.

Leads the strategy, governance, operations, security, support, release management, integrations, data quality, and continuous improvement of the Oracle Fusion HCM platform. Partners with HR and business leaders to translate requirements into scalable solutions, drive adoption, evaluate AI capabilities, manage vendors and quarterly releases, and ensure reliable employee data and enterprise integrations. Leads and develops the Oracle HCM team while maintaining strong controls, documentation, and service delivery standards.

Conduct quality audits across support, sales, renewals, and underwriting teams; evaluate compliance and customer interactions; validate AI-generated evaluations; refine scorecards and calibration processes; identify trends, risks, and process gaps; report findings; investigate root causes; and support process improvements and QA technology implementation while maintaining appropriate human oversight.

Architect and build a cross-platform design product spanning mobile, desktop, web, cloud services, connected cutting machines, and hardware integrations. Lead AI-native engineering practices, LLM feature integration, architecture governance, secure and reliable connectivity, backend APIs, large-scale modernization, and safe releases. Partner across product, design, QA, firmware, manufacturing, and security while mentoring engineers and remaining approximately 90% hands-on.

Build unified structured and unstructured data pipelines, predictive and prescriptive analytics, churn models with quantified uncertainty, and production LLM agents. Own enterprise AI architectures, RAG systems, MLOps and LLMOps standards, evaluation, monitoring, cost optimization, security, and reliability. Partner with business stakeholders to translate ambiguous problems into scalable AI solutions and document reference architectures adopted by other teams.

Leads AI-enabled operational transformation by identifying workflow improvements, designing and deploying Copilot-driven workflows, task-specific agents, and automated processes. Partners with operations, technology, risk, and platform teams to ensure compliant, scalable solutions. Tracks efficiency, quality, capacity, and adoption outcomes while driving implementation beyond pilots. Coaches teams, delivers hands-on training, and reinforces sustained AI adoption across operational functions.

Leads customer-facing AI pre-sales engagements and designs tailored enterprise AI architectures. Advises executive stakeholders on AI strategy, ROI, governance, secure LLM integration, RAG, cloud deployment, networking, datacenter infrastructure, and conversational or agentic AI. Partners with sales, engineering, and technical domain teams to evolve AI offerings, guide digital transformation, and promote scalable, ethical, high-performance deployments.

Leads AI, machine learning, and Generative AI engagements from opportunity discovery through solution design, prototyping, evaluation, and deployment readiness. Responsibilities include architecture, RAG and agent development, model evaluation, prompt engineering, governance, monitoring, documentation, client advising, proposal support, and team coaching. The role requires balancing hands-on technical leadership, responsible AI practices, commercial judgment, and stakeholder communication across complex client environments.

Leads AI, machine learning, and Generative AI engagements from opportunity discovery through solution design, evaluation, deployment readiness, governance, and adoption. Designs and reviews RAG assistants, document intelligence, agents, and analytics applications; advises on models, platforms, architecture, responsible AI, MLOps, and LLMOps. Partners with senior clients, manages technical quality and delivery workstreams, develops proposals and reusable assets, and coaches junior team members.