Director, AI & Agentic Engineering
Salary not listed • 135 W 26th Street, New York, NY 10001; Montréal, Quebec, Canada • Full-time
Posted 3mo ago
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Job Location
135 W 26th Street, New York, NY 10001; Montréal, Quebec, Canada
Tech Stack
Remote Work Policy
On-site
Employment Type
Full-time
Categories
AI Agent Engineer
About the job
Artefact, a global consulting firm specializing in data, analytics, and AI, is seeking a Director, AI & Agentic Engineering to lead a team in designing and delivering production-grade AI solutions. This role involves driving the architecture and implementation of everything from classical machine learning models to advanced LLM-powered applications and their supporting pipelines. You will provide senior technical judgment, collaborate closely with clients and business stakeholders, and play a key role in pre-sales activities, including shaping proposals and solution designs. The position requires embedding context engineering, agent harnesses, and fine-tuning practices into all solutions, while reporting on strategy and priorities to senior AI/technology leadership.
Responsibilities
- Lead the design, build, and optimization of production AI systems, including classical machine learning models, LLM applications, and agentic systems, ensuring scalability, reliability, and cost-efficient inference.
- 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, encompassing orchestration layers, evaluation frameworks, guardrails, and observability, to ensure LLM systems are reliable, safe, and measurable in production.
- Lead the design and operation of fine-tuning and model adaptation pipelines, including training data curation, supervised fine-tuning, evaluation, and deployment.
- Architect and deploy solutions using 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, setting technical standards and fostering best practices.
- Support pre-sales activities, including scoping engagements, building demos and proofs of concept, and presenting solution architectures to prospective clients.
- Oversee the development of classical and modern ML models, selecting appropriate techniques for business problems.
- Partner with senior leadership to shape GenAI architecture direction, tooling decisions, and platform roadmaps.
Requirements
- 8+ years of software engineering and AI experience, with at least 2-3 years focused on LLM architecture, agentic design, and harness & context engineering.
- Strong expertise in generative AI/LLM engineering (context engineering, agent harnesses, RAG, agentic coding) and cloud-native software architecture with proven production deployments.
- Master’s degree (or higher) in computer science, software engineering, or a related field.
- Hands-on command of agentic SDKs (LangGraph/LangChain, Google ADK, Claude Agent SDK) and agentic coding tools (Claude Code, Gemini CLI, Cursor).
- Proficiency with modern full-stack frameworks (TypeScript/React front ends; Python/Node backends).
- Experience designing cloud architectures: microservices, serverless, containers/Kubernetes, CI/CD, and infrastructure as code.
- Solid grasp of AI system design: agents, tool use, evaluation harnesses, guardrails, observability, and LLMOps.
- Experience with data & context modeling and ingestion/processing pipelines on data lakes and data warehouses, including vector and graph storage strategies.
- 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 activities.
- 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.