Company Overview

Artefact is a next‑generation consulting firm headquartered in Paris, specializing in data, analytics and AI consulting, dedicated to transforming data into business impact. We recently launched in the US with offices in New York City and Los Angeles and are expanding our founding team.

Role Overview

As Lead AI & Machine Learning Engineering Manager, you will lead a team of AI & ML engineers and managers, driving the design and delivery of production‑grade AI solutions—from classical machine learning models to LLM‑powered applications—and the pipelines that power them.

Responsibilities

- AI & ML Solution Architecture: 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.
- Context Engineering: Define and standardize context engineering practices—prompt and system design, RAG architectures, vector stores, memory management, and tool/function calling—so models receive the right information at the right time.
- Harness Engineering: Direct the build of robust agent harnesses—orchestration layers, evaluation frameworks, guardrails, and observability—that make LLM systems reliable, safe, and measurable in production.
- Fine‑Tuning Pipelines: Lead the design and operation of fine‑tuning and model adaptation pipelines—training data curation, supervised fine‑tuning, evaluation, and deployment—to specialize models for client use cases.
- Platform Stack: Architect and deploy solutions on Google Gemini Enterprise and Vertex AI as the primary stack, applying working knowledge of Microsoft AI Foundry and AWS Bedrock where client contexts require.
- Team Leadership: Manage, mentor,



and develop a team of AI & ML engineers; set technical standards and foster best practices and knowledge sharing.
- Pre‑Sales & Business Development: Support pre‑sales activities—scoping engagements, building demos and proofs of concept, and presenting solution architectures to prospective clients alongside account teams.
- Machine Learning Modeling: Oversee the development of classical and modern ML models—predictive modeling, forecasting, recommendation, and deep learning—choosing the right technique for each business problem, LLM or not.
- Contributing to AI Strategy: Partner with senior leadership to shape GenAI architecture direction, tooling decisions, and platform roadmap within your area.

Qualifications

- Substantial Data Science and machine learning background with 8+ years of experience, including 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; basic working knowledge of Microsoft AI Foundry and AWS Bedrock.
- Experience leading and growing engineering teams, and 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 workplace.

Preferred

- Google Gemini Enterprise ecosystem (Vertex AI, Agent Builder) as the primary stack; basic knowledge of Microsoft AI Foundry and AWS Bedrock.

Why Join Us

- There is always a way: We're from the breed of does, of diggers, of makers. Because ideas are valuable only if executed.
- Client trust is won on the field: Addressing client needs flows better hands on at their side.
- If not used, it is useless: Our love for technology translates into a steep desire for adoption, true brilliance is about impact.
- If not shared, our work is not done: Sharing knowledge is the best way to button up a mission, benefitting clients and colleagues.
- We learn everyday: Tech is a land where everything moves at the speed of light, you better be ready to challenge yourself.

Compensation and Benefits

The estimated base compensation for this role starts at $200,000 (NYC location). Individual compensation is determined by skills, qualifications, and experience. In addition, this role is eligible for competitive benefits.

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📌 Director, AI Engineering (Montreal)
🏢 Artefact
📍 Montreal