Director, AI & Data Science
About The Position
Artefact is a next-generation consulting firm, specializing in data, analytics & AI consulting, dedicated to transforming data into business impact across the entire value chain of organizations. Founded and headquartered in Paris, Artefact has 2000 employees across 36 offices globally, focused on accelerating digital transformation. They utilize state-of-the-art data technologies, lean AI agile methodologies, and cohesive teams of business consultants, data analysts, data scientists, data engineers, and digital experts. Artefact designs data-based solutions with a business-centric approach and delivers tangible results, leveraging deep AI expertise from over 1000 clients worldwide. The company has recently launched in the US with offices in NYC and Los Angeles and is seeking to build its founding team.
Requirements
- Substantial Data Science and machine learning background with 8+ years of experience.
- At least 2–3 years working on LLM architecture, agentic design, and harness & context engineering.
- Expertise in generative AI/LLM engineering (context engineering, agent harnesses, RAG, and fine-tuning) and in classical machine learning modeling, with proven production deployments.
- Master’s degree (or higher) in computer science, engineering, statistics/mathematics, or a related field.
- Hands-on command of core machine learning libraries (scikit-learn, XGBoost, etc.), agentic SDKs (LangGraph/LangChain, Google ADK, Claude Agent SDK), and fine-tuning frameworks (PyTorch, TensorFlow).
- Experience building fine-tuning pipelines end to end: training data curation, supervised fine-tuning, evaluation, and deployment.
- Solid grasp of AI system design: ML model lifecycle (MLOps), agents, tool use, evaluation harnesses, guardrails, and observability.
- Deep experience with Google Gemini Enterprise / Vertex AI.
- Experience leading and growing engineering teams.
- Experience supporting pre-sales: proposals, demos, and solution scoping with clients.
- Excellent communication skills and comfort collaborating across teams and with stakeholders.
- Strong business acumen with an interest in business-facing work.
- Adaptability and a start-up mentality to thrive in a dynamic environment.
Nice To Haves
- Basic working knowledge of Microsoft AI Foundry and AWS Bedrock.
- Google Gemini Enterprise ecosystem (Vertex AI, Agent Builder) as the primary stack.
Responsibilities
- Lead a team of AI & machine learning engineers and managers, driving the design and delivery of production-grade AI solutions (classical machine learning models to LLM-powered applications) and their supporting pipelines.
- Provide senior technical judgment on architecture and model decisions.
- Partner closely with clients and business stakeholders, including hands-on pre-sales work shaping proposals and solution designs.
- Define how context engineering, agent harnesses, and fine-tuning practices are embedded into every solution.
- Report into senior AI/technology leadership on strategy and priorities.
- Lead the design, build, and optimization of production AI systems (classical machine learning models, LLM applications, and agentic systems), ensuring scalability, reliability, and cost-efficient inference.
- Define and standardize context engineering practices (prompt and system design, RAG architectures, vector stores, memory management, and tool/function calling).
- Direct the build of robust agent harnesses (orchestration layers, evaluation frameworks, guardrails, and observability) for LLM systems.
- Lead the design and operation of fine-tuning and model adaptation pipelines (training data curation, supervised fine-tuning, evaluation, and deployment).
- Architect and deploy solutions on Google Gemini Enterprise and Vertex AI, with working knowledge of Microsoft AI Foundry and AWS Bedrock.
- Manage, mentor, and develop a team of AI & ML engineers, setting technical standards and fostering best practices.
- Support pre-sales activities, including scoping engagements, building demos and proofs of concept, and presenting solution architectures.
- Oversee the development of classical and modern ML models (predictive modeling, forecasting, recommendation, deep learning).
- Partner with senior leadership to shape GenAI architecture direction, tooling decisions, and platform roadmap.
Benefits
- Competitive benefits
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What This Job Offers
Job Type
Full-time
Career Level
Director
