AI Solutions Delivery Lead

4e1f673a-e23b-4f79-98bf-9967bc802aac • Dallas, TX

10h

About The Position

Applied Digital is seeking an AI Solutions Delivery Lead to help teams improve how work gets done using practical, secure AI and automation. This hands-on product and delivery role turns high-value business problems into working solutions that people use, with a focus on improving specific workflows, reducing manual effort, and helping teams make faster, better-informed decisions.

The role partners with process owners and subject matter experts across Technology and business teams to understand workflows, define useful outcomes, and confirm data and system access. The lead delivers solutions in small, testable stages, from prototype through rollout, user adoption, and measurement. They coordinate with owners of relevant platforms, systems, data, and security across Corporate IT, Systems, Network, DCIS/Controls, Cybersecurity, and business teams, using internal capabilities and vendors as appropriate.

The position leads AI and automation initiatives from discovery through rollout and ongoing improvement. Solutions may include AI-enabled applications, agents, automations, and workflow utilities connected to approved enterprise systems and data sources. The role ensures outputs are reviewable and useful within actual workflows, supports user testing and adoption, measures outcomes, and applies responsible practices for security, privacy, auditability, and cost control. The description requires a bachelor’s degree or equivalent experience, at least three years delivering technology products, automation, integrations, or operational improvement initiatives, and at least two years of hands-on applied AI or intelligent automation experience.

Requirements

• Bachelor’s degree in computer science, engineering, information systems, business, or a related field, or equivalent experience.
• At least 3 years of experience delivering technology products, automation, integrations, or operational improvement initiatives.
• At least 2 years of hands-on experience delivering applied AI or intelligent automation solutions, including at least one solution used in a real business workflow.
• Experience taking solutions beyond a demo, including responsibility for testing, deployment, user feedback, and ongoing improvement.
• Working knowledge of current AI solution patterns, such as LLM APIs, retrieval-augmented generation, tool or function calling, and workflow automation.
• Experience connecting applications and data through APIs, identity controls, and enterprise platforms.
• Ability to investigate data quality and access early, validate assumptions with system owners, and explain limitations clearly.
• Strong communication and facilitation skills, including the ability to work with frontline users, technical teams, and senior leaders.
• Ability to define practical measures of success and use them to guide delivery decisions.
• Working knowledge of enterprise security and responsible AI practices, including access control, sensitive data handling, human review, and auditability.

Nice To Haves

• Experience in construction, engineering, infrastructure, manufacturing, finance, or another operations-heavy environment.
• Experience working with complex projects, contract, invoice, procurement, or operational records.
• Experience with one or more of Azure AI, Palantir Foundry, UiPath, Copilot Studio, GrokBot, or Cursor.
• Experience with Python, TypeScript, or another language for prototypes, data analysis, or integrations.
• Familiarity with model evaluation, retrieval quality testing, monitoring, and production support.
• Experience coordinating internal stakeholders and external implementation partners.
• Master’s degree in a technical or business field.

Responsibilities

• Partner with teams in construction, finance, engineering, and operations to identify repetitive, time-consuming, or error-prone work.
• Define use cases with a business owner, clear user need, baseline, and measurable target.
• Confirm early that required data, system access, and subject matter expertise are available, and surface gaps and dependencies.
• Prioritize a focused portfolio based on business value, feasibility, risk, and time to deliver.
• Identify workflow steps where teams search records, reconcile information, prepare updates, track actions, or move work between systems.
• Build and improve practical internal tools, including AI-enabled applications, agents, automations, and workflow utilities.
• Develop tools that support activities such as reviewing invoices or change orders, checking project requirements, tracking materials, resolving exceptions, and preparing operational decisions.
• Ensure tools provide clear outputs, links to source information, visible exceptions, and an identified next action or owner.
• Measure whether full tasks are completed faster, with less rework or fewer errors, and work with users to test, refine, document, and support tools after rollout.
• Lead focused AI and automation initiatives from discovery through rollout and ongoing improvement.
• Break ambiguous requests into small deliverables users can test and provide feedback on.
• Build prototypes or working solutions directly where practical, coordinating with internal technology owners or external partners when needed.
• Connect solutions to approved enterprise systems and data sources, including document repositories, ERP and project systems, databases, and collaboration tools.
• Keep business owners and technology stakeholders informed about scope, data, access, timing, and delivery risks.
• Test solutions with real users and representative data before making claims about accuracy, savings, or readiness.
• Establish suitable evaluation methods, including accuracy, coverage, time saved, exception detection, and user adoption.
• Work with business owners to verify results against source records and agree on successful outcomes.
• Ensure business owners and users participate in validation, make timely decisions, and support adoption.
• Provide training, documentation, feedback channels, and clear ownership for ongoing support.
• Monitor performance after rollout and refine or retire solutions based on evidence of value.
• Work with Security, Legal, technology owners, and business stakeholders to address data access, privacy, retention, auditability, and model-use requirements.
• Use approved platforms and internal capabilities where suitable, and recommend vendors or custom development when needed.
• Apply practices for identity, secrets management, logging, monitoring, and cost control.
• Create reusable delivery patterns, evaluations, and documentation to support responsible AI use across teams.
• Report progress, decisions, risks, and realized outcomes to business and executive stakeholders.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level