Overview In this role, you lead a team of AI & ML engineers to design and deliver production-grade AI systems, from traditional models to LLM-driven applications. You shape architecture, drive context and harness engineering, and guide fine-tuning pipelines while collaborating with clients and senior leadership. You influence AI strategy and platform roadmap, ensuring scalable, cost-efficient solutions. This is a high-impact role within Artefact's US expansion, blending technical leadership with business-facing work.
Compensation / Benefits- competitive benefits
- base compensation starting at $200,000 (NYC)
- hybrid/work location flexibility
- opportunity to contribute to US expansion
- working with world-class clients
Responsibilities- Lead design, build, and optimization of production AI systems (classical ML, LLM apps, agentic systems)
- Define and standardize context engineering practices (prompt/system design, RAG, vector stores)
- Direct development of robust agent harnesses (orchestration, evaluation, guardrails, observability)
- Oversee fine-tuning and model adaptation pipelines (data curation, supervised fine-tuning, deployment)
- Architect and deploy solutions on Google Gemini Enterprise and Vertex AI; leverage Microsoft AI Foundry and AWS Bedrock when needed
- Manage and mentor a team of AI & ML engineers; set technical standards and promote knowledge sharing
- Support pre-sales activities (scoping, demos, proofs of concept, solution scoping with clients)
- Oversee ML modeling workflows (predictive, forecasting, recommendation, deep learning)
- Contribute to AI strategy and GenAI architecture direction and platform roadmap
Key requirements- 8+ years in Data Science/ML with hands-on production deployments
- 2-3 years working on LLM architecture, agentic design, and harness & context engineering
- Expertise in generative AI/LLM engineering (context, agents, RAG, fine-tuning) and classical ML modeling
- Master's degree in a related field
- Proficiency with ML libraries (scikit-learn, XGBoost) and agentic SDKs (LangGraph/LangChain, Google ADK, Claude Agent SDK)
- Experience building end-to-end fine-tuning pipelines (data curation, supervised fine-tuning, evaluation, deployment)
- Strong grasp of ML lifecycle, MLOps, agents, tools, guardrails, observability
- Deep experience with Google Gemini Enterprise / Vertex AI; basic knowledge of Microsoft AI Foundry and AWS Bedrock
- Proven leadership of engineering teams and involvement in pre-sales activities
- Excellent communication across teams and stakeholders
- Strong business acumen with a client-focused mindset
- Adaptability and startup mentality
- Google Gemini Enterprise
- Vertex AI
- LangChain/LangGraph
