AI Practice Consultant

A client sees an opportunity for AI but needs to know what is worth building, what it will take, and whether it will deliver. You’ll work through those questions with them and build the solution.

As an AI Practice Consultant at Digineer, you’ll partner directly with the AI Practice Leader across opportunity shaping, discovery, proposals, solution design, and implementation. Client advisory and presales will be a significant, ongoing part of your work. You’ll lead conversations with business stakeholders, explain technical tradeoffs, and turn unclear problems into credible recommendations.

You’ll also design and deliver AI applications, agentic systems, and supporting data pipelines. This position requires demonstrated experience shipping AI solutions and the ability to connect engineering decisions to measurable business value.

You’ll apply and deepen your expertise in Knowledge Engineering, including semantic modeling and ontology development that support advanced AI reasoning. Prior experience in this discipline is required, along with curiosity, sound problem solving, and a commitment to continued learning. You’ll work directly with the AI Practice Leader to apply that expertise to client engagements.

Partner with the AI Practice Leader to qualify opportunities and assess where AI can produce business value.

Facilitate discovery sessions that uncover business needs, constraints, and measures of success.

Shape solution approaches, estimate effort, and develop proposals.

Present recommendations to prospective clients, explaining feasibility, tradeoffs, and expected outcomes.

Advise clients on where AI is appropriate and where another approach makes more sense.

Build trusted relationships with executives, business users, and technical teams.

Facilitate workshops and lead technical working sessions.

Translate complex technical concepts into clear business decisions.

Surface risks, challenge assumptions, and keep stakeholders aligned as requirements evolve.

Design and implement AI applications, agentic systems, and supporting data pipelines.

Connect and transform enterprise data for use in AI workflows.

Own solution work streams from proof of concept through production handoff.

Evaluate solution performance against technical requirements and business objectives.

Maintain high standards for engineering quality, testing, documentation, and delivery.

Develop semantic models, ontologies, and knowledge representations in collaboration with the AI Practice Leader.

Apply Digineer’s Knowledge Engineering methodology to client solutions.

Represent business concepts and relationships in ways that support AI reasoning.

At least 5 years of professional experience, including 3 or more years designing, building, and delivering AI solutions that produced measurable business value.

Demonstrated ability to independently take an AI solution from concept through delivery.

Prior experience in Knowledge Engineering, including semantic modeling and ontology development.

Experience with modern LLM ecosystems, including prompt engineering, retrieval augmented generation (RAG), agent frameworks, Model Context Protocol (MCP), and model evaluation, along with hands on use of AI coding agents such as Claude Code in delivery.

Strong data integration and engineering skills across enterprise data sources.

Excellent written and verbal communication, with both the ability and desire to work directly with clients.

Experience facilitating discussions, explaining technical concepts to nontechnical audiences, and building trusted relationships.

Curiosity, sound problem solving, and the ability to learn unfamiliar technologies quickly.

Ability to work through ambiguity and apply…