Principal Data Scientist, Agentic AI Technical Lead

This is a fully remote position, open to applicants in Canada.

📋 Description

• Oversee the technical aspects of all agentic AI workstreams, from problem identification and design to evaluation, deployment, and ongoing operations.

• Develop technical strategies and reference architectures for agentic systems, such as multi-agent orchestration, tool and function calling, RAG patterns, vector databases, embeddings, and streaming responses.

• Manage the technical delivery across various streams, addressing obstacles and coordinating dependencies.

• Establish standards for model development, experimentation, and processes that transition research to production.

• Create evaluation frameworks for LLM and agent performance, focusing on quality, safety, hallucination, cost, and latency.

• Guide the development of scalable ML platforms, pipelines, and workflow orchestration for event-driven, asynchronous operations.

• Ensure the reliability, security, scalability, observability, monitoring, and debugging of production systems.

• Act as the technical representative of the AI/ML program to senior client stakeholders.

• Collaborate with executive leadership to co-define the AI roadmap.

• Simplify complex technical concepts for executive, engineering, and business audiences.

• Align data science, engineering, product, and business teams around common priorities and measurable outcomes.

• Lead and influence a large, multi-team delivery organization.

• Define and advocate for data science and AI engineering standards.

• Review and enhance work quality across teams.

• Mentor technical leads and senior practitioners.

• Make critical, program-wide technical decisions.

• Drive the long-term technical vision for the agentic AI practice.

⛳️ Requirements

• Over 12 years of experience in data science and AI/ML.

• Proven history of transitioning AI systems from research to production at an enterprise scale.

• Demonstrated ability to lead technical delivery across multiple concurrent workstreams or teams.

• Experience in leading or technically overseeing large, multi-team programs, including managing technical risks, dependencies, and ensuring delivery quality.

• Exceptional skills in stakeholder management and communication, with established credibility among senior executives and client leadership.

• Practical experience with LLM and agentic systems, including prompt engineering, function/tool calling, multi-agent orchestration, RAG architectures, vector databases, embeddings, and streaming LLM responses.

• Extensive knowledge in model evaluation, experimentation design, and applied statistics, including evaluation methods for generative and agentic systems.

• Strong command of Python and the modern data science and ML stack.

• Expertise in MLOps and AI infrastructure, encompassing model versioning, monitoring, deployment automation, and reproducibility.

• Solid foundations in software engineering, including system design, API design, code quality, and unit testing practices.

• Experience with distributed systems, event-driven architectures, and workflow orchestration tools.

• Comprehensive familiarity with AWS, particularly Amazon Bedrock; working knowledge of other cloud platforms is a plus.

• Understanding of SQL and NoSQL databases, including scalable design patterns.

• Working knowledge of AI governance, responsible AI, and compliance considerations in production environments.

• Experience supporting AI programs in regulated industries such as life sciences, healthcare, or financial services.

• Background in consulting or client-facing technical leadership roles.

• Experience in fine-tuning, evaluation automation, or ensuring agent safety and guardrails.

🏝️ Benefits

• Production-ready AI delivered within 30 to 45 days.

• Opportunity to engage with AI systems that integrate into enterprise operations.

• Chance to collaborate with experienced teams averaging over fifteen years of expertise.