Director, AI Engineering
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Key skills for this role
About the Role
Artefact is looking for a Director of AI Engineering to lead a team of AI/ML engineers and managers, driving production-grade AI solutions from classical ML to LLM-powered applications.
Key Skills for This Role
Responsibilities
- Lead a team of AI & machine learning engineers and managers, driving the design and delivery of production grade AI solutions
- Define and standardize context engineering practices including prompt and system design, RAG architectures, vector stores, memory management, and tool/function calling
- Direct the build of robust agent harnesses including orchestration layers, evaluation frameworks, guardrails, and observability
- Lead the design and operation of fine tuning and model adaptation pipelines
- Architect and deploy solutions on Google Gemini Enterprise and Vertex AI as the primary stack
- Manage, mentor, and develop a team of AI & ML engineers; set technical standards and foster 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 including predictive modeling, forecasting, recommendation, and deep learning
- Partner with senior leadership to shape GenAI architecture direction, tooling decisions, and platform roadmap
Requirements
- 8+ years of data science and machine learning 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, fine tuning) and classical ML modeling with production deployments
- Master's degree or higher in computer science, engineering, statistics/mathematics, or related field
- Hands on command of core ML libraries (scikit learn, XGBoost), agentic SDKs (LangGraph/LangChain, Google ADK, Claude Agent SDK), and fine tuning frameworks (PyTorch, TensorFlow)
- Experience building fine tuning pipelines end to end
- 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
- Excellent communication skills and comfort collaborating across teams and with stakeholders
Full Job Posting
About The Job
- Artefact is a next generation consulting firm specializing in data, analytics & AI consulting, with 2000 employees across 36 offices.
- We help clients grow their data and digital capabilities, designing data based solutions with a business centric approach.
What You Will Be Doing
- Lead a team of AI & machine learning engineers and managers, driving the design and delivery of production grade AI solutions from classical ML to LLM powered applications.
- 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.
- 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 as the primary stack, with working knowledge of Microsoft AI Foundry and AWS Bedrock.
- Manage, mentor, and develop a team of AI & ML engineers; set technical standards and foster best practices.
- Support pre sales activities: 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, and deep learning.
- Partner with senior leadership to shape GenAI architecture direction, tooling decisions, and platform roadmap.
What We Are Looking For
- 8+ years of data science and machine learning 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, fine tuning) and classical ML modeling with proven production deployments.
- Master's degree or higher in computer science, engineering, statistics/mathematics, or related field.
- Hands on command of core ML libraries (scikit learn, XGBoost), agentic SDKs (LangGraph/LangChain, Google ADK, Claude Agent SDK), and fine tuning frameworks (PyTorch, TensorFlow).
- Experience building fine tuning pipelines end to end.
- 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.
Why Join Us
- We are united by our values: There is always a way, Client trust is won on the field, If not used it is useless, If not shared our work is not done, We learn everyday.
- The estimated base compensation for this role starts at CAD 200,000 (NYC location). Individual compensation is determined by skills, qualifications, and experience.
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