Director, AI & Data Science

Find out more at artefact.com.

What you will be doing

You will lead a team of AI & machine learning 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. You’ll bring senior technical judgment to architecture and model decisions, partner closely with clients and business stakeholders — including hands-on pre-sales work shaping proposals and solution designs — and define how context engineering, agent harnesses, and fine-tuning practices get embedded into every solution, while reporting into senior AI/technology leadership on strategy and priorities.

• AI & ML Solution Architecture: Leading 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: Defining and standardizing 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: Directing 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: Leading 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: Architecting and deploying 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: Managing, mentoring, and developing a team of AI & ML engineers; setting technical standards and fostering best practices and knowledge sharing.
• Pre-Sales & Business Development: Supporting pre-sales activities — scoping engagements, building demos and proofs of concept, and presenting solution architectures to prospective clients alongside account teams.
• Machine Learning Modeling: Overseeing 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: Partnering with senior leadership to shape GenAI architecture direction, tooling decisions, and platform roadmap within your area.

What we are looking for

• The ideal candidate has a 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 environment.