(1114575) Generative AI Adoption Specialist

Diversified Services Network, Inc.•Irving, TX

1d•$85,000 - $90,000•Onsite

About The Position

The Generative AI Adoption Specialist is an onsite individual contributor who helps business teams understand, adopt, and gain value from Generative AI tools and agentic capabilities. Working closely with the Data Science Pod Lead, AI Product Owners, AI Architects, and business partners, this role translates business needs into practical use cases, guides teams through experimentation and adoption, and connects users with approved tools, platforms, and specialist support, ensuring every solution aligns with enterprise standards, security requirements, and Responsible AI principles.

Requirements

Minimum Bachelor's degree, preferably in computer science, engineering, information systems, statistics, mathematics, or a related quantitative field.
2+ years of professional experience required.
Working knowledge of GenAI tools and business productivity technologies, with the ability to configure, test, demonstrate, troubleshoot, and document prompts, assistants, agents, and workflows.
Hands-on skill in prompt design, system instructions, knowledge grounding, agent configuration, structured outputs, and output evaluation.
Solid understanding of AI, GenAI, and agentic concepts, risks, opportunities, and limitations, and how to apply them responsibly to achieve business outcomes.
Digital literacy across collaboration platforms, workflow tools, data sources, APIs, and basic scripting or analytical tools.
Strong verbal and written communication skills.
Patient, self-motivated, and collaborative team player.

Nice To Haves

Master's degree in a technical or quantitative field.
Knowledge of the AI-enabled solution lifecycle, from discovery and use-case definition through validation, approval, deployment, measurement, and retirement.
Experience working within structured delivery and governance methods for GenAI solutions, including intake, prioritization, testing, risk review, change management, release, and benefits tracking.
Python programming experience (NumPy, pandas, etc.) applied to business challenges.
Experience with cloud technologies such as AWS, Azure, or Google Cloud.

Responsibilities

Align business engagement and enablement activities with the pod's direction, priorities, governance, and expected outcomes.
Partner with business stakeholders to understand user needs, desired outcomes, adoption barriers, success measures, and value hypotheses.
Identify and document business problems, process opportunities, and potential applications of GenAI tools or agentic capabilities.
Evaluate opportunities from user, business value, data, risk, governance, technology, adoption, and support perspectives.
Develop and compare alternative approaches, including existing enterprise tools, configurable agents, reusable patterns, process changes, or referral to specialist delivery teams.
Apply discovery, facilitation, experimentation, and evaluation techniques to guide recommendations and adoption decisions.
Explain GenAI and agentic concepts, common use cases, tool capabilities, limitations, risks, and the role of human oversight in clear language for technical and non-technical audiences.
Demonstrate how copilots, assistants, agents, knowledge grounding, prompts, and AI-enabled workflows can support everyday business activities.
Point business users to the right enterprise guidance, learning resources, approved tools, and specialist support.
Create and share practical examples, reusable patterns, and best practices that help teams adopt GenAI responsibly and effectively.
Collaborate with architecture, platform, data, engineering, cybersecurity, legal, privacy, Responsible AI, learning, and change-management teams as needed.
Work with users to reproduce issues, clarify expected outcomes, and distinguish between user guidance, configuration, data, platform, or integration problems.
Answer questions on tool features, prompt behavior, knowledge grounding, access, compatibility, workflow design, and appropriate usage.
Analyze prompts, configurations, outputs, diagnostics, logs, test cases, and user feedback to troubleshoot issues, escalating to specialist teams when needed.
Document and communicate issues, resolution steps, workarounds, and lessons learned to strengthen ongoing adoption and support.