Lead AI/ML and MLOpos Consultant

A Lead AI/ML & MLOps Engineer to join our Canadian team. This is a senior, dual-purpose role:

1. Delivery leadership: leading the technical execution of AI and ML engagements for our clients, from data foundations through model deployment and operation.

2. Pre-sales and pipeline partnership: working alongside our sales organisation to shape, scope, and win new opportunities, with a specific focus on supporting deals that move through our partners motion.
   

You will be the senior technical voice in the room when we design AI/ML engagements: validating architectures, choosing tooling, scoping work, and standing behind the engineers who build it. You will also be a credible counterpart to client CTOs, data leaders, and partner technical sellers.

Key Responsibilities
Delivery and technical leadership

• Lead the architecture and hands-on implementation of end-to-end ML systems: data ingestion, pipelines, feature stores, training, evaluation, serving, and monitoring.

• Own technical decisions across the full stack, data platform, training environment, model serving, and MLOps tooling.

• Set engineering standards for ML projects: experiment tracking, model versioning, reproducibility, governance, observability, drift monitoring, and CI/CD for ML.

• Coach and uplift other engineers on the team in modern ML and MLOps practices.

• Stay accountable for quality, security, and operational soundness of what we ship.

Pre-Sales and pipeline support

• Partner with the sales leadership team across pre-sales activity: discovery calls, scoping workshops, technical briefings, and LOE preparation.

• Lead architecture and solutioning conversations with prospects and customers, translate business problems into credible, defensible technical approaches.

• Provide dedicated technical support to opportunities flowing through the partners sales process, including positioning their products as part of broader data and AI architectures, joint solutioning sessions, and partner-aligned proposals.

• Contribute to thought leadership and demand generation: blog posts, webinars, capability decks, conference talks, and reference architectures.