AI Functional Technical Consultant

Onset LLC•Dallas, TX

About The Position

The AI Functional Technical Consultant serves as the bridge between business stakeholders and technical AI/ML delivery teams. This person translates business processes and functional requirements into AI-driven solutions, configures and customizes AI platforms, and ensures solutions are both technically sound and aligned with client business objectives. The ideal candidate combines domain/functional expertise (Telecommunication domain preferred) with hands-on technical fluency in AI tools, integrations, and data pipelines.

Requirements

Bachelor's degree in Business, Computer Science, Information Systems, or related field (Master's a plus)
3–7 years of experience in functional/technical consulting, business analysis, or solution implementation
Hands-on experience and strong AI foundation knowledge on Agentic AI, Langchain, Deep Agents, Google ADK and CrewAI
Strong understanding of business processes in at least one functional domain (finance, supply chain, HR, sales, customer support, etc.)
Experience with requirements gathering, process mapping, and solution design methodologies
Familiarity with APIs, data integration concepts, and basic scripting (Python, SQL) for configuration/validation
Excellent communication skills — able to translate technical concepts for non-technical stakeholders and vice versa
Experience with project delivery methodologies (Agile, Scrum, or Waterfall)

Nice To Haves

Certifications in relevant AI platforms or cloud providers (Azure, AWS, GCP)
Change management or training/enablement experience
Telecommunications Industry-specific expertise

Responsibilities

Gather, analyze, and document business requirements; translate them into functional and technical specifications for AI/ML solutions
Configure, customize, and implement AI platforms (e.g., generative AI, LLM-based agents, predictive analytics, RPA+AI hybrid solutions) to meet client needs
Design and validate AI workflows, prompts, decision logic, and integration points with existing enterprise systems (ERP, CRM, data warehouses)
Conduct fit-gap analysis between out-of-the-box AI capabilities and client-specific requirements
Collaborate with data engineers, ML engineers, and solution architects to ensure technical feasibility and scalability
Lead or support workshops, demos, and UAT (user acceptance testing) sessions with business stakeholders
Develop functional design documents, process flows, test scripts, and training materials
Monitor AI solution performance post-deployment; recommend optimizations based on usage data and business outcomes
Ensure solutions comply with data governance, security, and ethical AI standards
Act as a trusted advisor to clients on AI adoption strategy, change management, and best practices