Strategy and Technical Leadership

• Set strategic vision and direction for Agentic Proposal Workflows, ensuring alignment with enterprise priorities to maximize business impact.
• Define and execute the roadmap for the Agentic Proposal Workflows suite, establishing policies and standards while anticipating industry shifts in multi-agent architectures.
• Serve as the executive champion for the Agentic AI Platform, articulating its value to senior stakeholders, influencing enterprise decision-making, and fostering a culture of AI innovation and accountability.

Applied Science and Systems Design

• Set the scientific and technical direction for the ML function, leading advancements in NLP, LLM fine-tuning, generative AI, and agentic systems.
• Oversee architecture and technical strategy for end-to-end ML workflows, including data pipelines, training, deployment, monitoring, and continuous improvement.
• Design and implement intelligent agent workflows, such as reasoning engines, planner-reflector loops, and adaptive feedback pipelines, while adapting emerging research into scalable production systems.

Leadership and Talent Development

• Build, scale, and mentor a world-class applied science organization across Canada, India, and the UK, including developing future managers and science leaders.
• Foster a high-performing culture centered on ownership, urgency, technical excellence, and continuous learning.
• Attract, retain, and grow top applied science talent in a globally distributed environment.

Delivery and Operational Excellence

• Oversee planning, prioritization, and execution of ML initiatives, managing dependencies, risks, and alignment with business goals.
• Establish robust evaluation pipelines, golden datasets, and measurement frameworks to ensure rigor and tie outcomes to business metrics.
• Champion operational excellence by embedding observability, drift and bias monitoring, and root cause analysis into ML systems and processes.
• Partner with Product, Design, and Engineering to integrate ML systems into workflows, communicate trade-offs, and deliver measurable customer impact.

Strategy and Technical Leadership Requirements

• Proven experience setting technical strategy for applied ML initiatives and aligning them with enterprise business priorities.
• Ability to influence executive stakeholders and articulate the value of AI platforms in driving organizational impact.

Applied Science and Systems Design Requirements

• Deep expertise in NLP, transformers, LLMs, retrieval-based methods, and multi-agent systems, with a track record of moving research into production.
• Strong programming and architecture skills, with hands-on experience in PyTorch, TensorFlow, and designing scalable ML services and APIs.

Leadership and Talent Development Requirements

• 4+ years leading applied ML teams, including experience mentoring managers and building globally distributed, high-performing organizations.
• Demonstrated success fostering cultures of accountability, technical excellence, and continuous learning.

Delivery and Operational Excellence Requirements

• Strong execution skills in planning, prioritization, and risk management for complex applied science initiatives.
• Experience implementing evaluation pipelines, monitoring systems, and operational processes that ensure both scientific rigor and production reliability.
• Ability to drive measurable customer and business outcomes through applied AI systems.

Work Model and Location

• Role based in Toronto, Ontario hub, working hybrid model with 3 days per week in a co-working space in downtown Toronto.
• Collaborate virtually across teams in Canada, UK, and India with core sync hours and focus time.
• Hybrid approach enables in-person collaboration and flexible work-from-home days.