AI & Data Consulting Manager

Artefact is a next-generation data and AI consulting firm dedicated to accelerating the adoption of data and AI to create measurable business impact across the full enterprise value chain.

We sit at the intersection of consulting, data science, AI technologies, data engineering, and digital transformation. We do not just advise — we build, implement, and deliver results our clients can measure. Our teams bring together consultants, data scientists, data engineers, AI engineers, analysts, and digital experts to solve complex business challenges with pragmatic, production-ready solutions.

As we continue to grow in the US, we are building a team of entrepreneurial data and AI talent who can help clients move beyond experimentation and into scalable, governed, value-generating AI adoption.

The Role

Artefact is looking for an AI & Data Consulting Manager: someone who runs projects autonomously, develops the people on them, grows the client relationship — and builds with AI along the way.
Managers at Artefact are AI-literate builders. You use AI tools every day to produce your own work faster and better, and when a recommendation needs proof, you can prototype it: open Claude Code or Gemini CLI and turn an idea into something the client can click on. We need someone who is not afraid of the terminal — someone who, with the help and guidance of AI, will build the thing rather than just describe it.

What You'll Do

• Manage projects end to end: structure sub-streams, distribute work fairly, set team OKRs, and give sponsors clear visibility.
• Build robust plans that anticipate deadlines, delays, and risks — and communicate them before they become surprises.
• Structure mission deliverables: write C-level executive summaries autonomously and build presentation storylines with partner support.
• Hold Artefact's quality bar on everything that leaves the team.
• Your recommendations are grounded in hands-on understanding of the AI stack.
• Define client needs through interviews with client teams and technology partners, and translate them into strategic data and AI recommendations.
• Prototype with AI tools — agentic coding tools like Claude Code, Gemini CLI, or Codex — to test feasibility and make ideas tangible in workshops and steering committees.
• Understand context engineering well enough to shape how clients connect AI to their data, documents, and systems (RAG, semantic layers, MCP).
• Maintain specialization in at least one AI platform ecosystem — Google (Gemini), Anthropic (Claude), or OpenAI — and keep it current.
• Make the people under your influence progress.