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Artefact

Data and AI-driven business transformation consulting

Manager, Forward Deployed Engineering

Engineering LeadershipConfirmed live in the last 24 hours
Full-timeUtrecht, NetherlandsNo salary listed

About the Job

Requirements

  • Six to nine years of experience in software or data engineering, including recent, substantial hands-on delivery with artificial intelligence and large language model-based systems, plus prior experience leading or managing engineers.
  • Strong hands-on experience with the Google AI stack, including Gemini models, Vertex AI, Gemini Enterprise, and ADK, with multiple solutions taken to production on Google Cloud Platform.
  • Strong programming background in Python and TypeScript or JavaScript, with enough depth to review architecture and code.
  • Experience building and consuming application programming interfaces, front-end development with React or similar, and at least one backend framework.
  • Hands-on experience with retrieval-augmented generation, embeddings, vector search, and at least one agentic framework such as Google ADK or LangGraph/LangChain.
  • Proven experience managing or leading a team of engineers, including staffing, performance, and development.
  • Experience owning senior-level client relationships, including scoping, expectation-setting, and escalation management.
  • Strong working experience with Google Cloud Platform; Azure or Amazon Web Services experience is a plus.
  • Fluency with agentic coding tools such as Claude Code, Gemini CLI, Codex, or Cursor.
  • Bachelor's or Master's degree in computer science, engineering, or a related field, or equivalent practical experience.

Responsibilities

  • Own technical delivery across one or more client engagements, including architecture decisions, technical risk, and quality standards.
  • Set direction on interface design using TypeScript and React, backend services using Python or Node, and the agentic and retrieval systems beneath them.
  • Review and unblock the team's work on orchestration, tool and function calling, memory, guardrails, and retrieval-augmented generation pipelines.
  • Make build-versus-buy and platform decisions that shape how a client's AI systems connect to its data and applications.
  • Set technical standards for building with Gemini models, Vertex AI, ADK, and Agent Engine.
  • Guide implementation and configuration of Gemini Enterprise, including Agent Designer, Inbox, agent sandboxes, and connector governance.
  • Make architecture decisions involving Vertex AI Search, RAG Engine, grounding with Google Search, and BigQuery as the data backbone.
  • Track Google's roadmap and releases, and decide when and how new capabilities are adopted into client work.
  • Set and enforce standards for evaluation suites, regression testing, and production monitoring of cost, latency, and quality across engagements.
  • Establish engineering practices across the team, including version control, code review, continuous integration and continuous delivery, and observability.
  • Make infrastructure and deployment decisions across Google Cloud Platform, Azure, or Amazon Web Services.
  • Own the health of the data pipelines feeding the team's AI systems.
  • Manage a team of Deployed AI Engineers, including staffing, workload, performance, and career development.
  • Hire, onboard, and grow engineers into Gemini Enterprise specialists.
  • Serve as the senior client-facing voice for engagements, communicating trade-offs, risk, and progress to client stakeholders and company leadership.
  • Support senior-level pre-sales by scoping solutions, sizing teams, and estimating delivery effort in partnership with consulting teams.
  • Set and scale internal accelerators, reusable components, and engineering standards across engagements.

Desired Qualifications

  • Experience with Azure or Amazon Web Services.

About the Company

Artefact

Data and AI-driven business transformation consulting

Artefact helps organizations use data and AI to transform their operations and decision-making. It provides end-to-end services across the data value chain, from strategy and data platform implementation to governance, advanced analytics, and sector-specific AI tools, delivered through consulting and project execution. The company works with industries like FMCG, retail, and luxury goods to optimize marketing performance, customer engagement, and ROI. Artefact differentiates itself by combining consulting expertise with data science and AI capabilities across multiple regions, offering integrated, sector-focused solutions rather than just advisory services. The main goal is to help clients adopt data-driven approaches to improve efficiency, decision quality, and marketing results at scale.

Company size
1,001-5,000
Company stage
IPO
Headquarters
Paris, France
Founded
1998

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