Senior AI Delivery Lead

On behalf of our oil & gas client, Vaquarii is seeking a Senior AI Delivery Lead for a 12-Month Contract with a high possibility of extension or conversion to full-time employment The perfect candidate will be facilitating sprint planning, daily stand-ups, sprint reviews, and retrospectives within a high-velocity AI prototyping environment where experiment cycles don’t behave like standard software delivery sprints. Services would be carried out though a Hybrid Work Schedule from their downtown Calgary headquarters.

Responsibilities:

• Serve as the operational glue of a four-person AI pod – the hiring manager’s description, not an embellishment.
• Will be working with a Data Scientist, ML Developer, and Data Engineer.
• This person establishes the sprint cadence, shapes the delivery model, and creates the conditions under which three senior technical practitioners can move fast without losing coherence.
• Facilitate sprint planning, daily stand-ups, sprint reviews, and retrospectives within a high-velocity AI prototyping environment where experiment cycles don’t behave like standard software delivery sprints. Inconclusive results are expected.
• Fail-fast is the model.
• Partner with the Product Owner to manage and prioritize an AI-focused backlog where the work ranges from classical ML forecasting models to agentic solution development and third-party vendor integrations.
• Remove impediments, manage cross-workstream dependencies, and mitigate delivery risks across three distinct technical disciplines simultaneously – data engineering, ML development, and data science.
• When three senior practitioners are in rapid experimentation mode under organizational scrutiny, this person holds the delivery discipline together.
• Track and report agile metrics – velocity, sprint progress, delivery outcomes – and produce concise, outcome-focused updates for director-level stakeholders.
• The hiring manager and project lead distill these upward to executives; this person’s output shapes what senior leadership sees about the pod’s progress.
• The ability to communicate technical complexity in business language is not a nice-to-have – it is the core of the stakeholder management function in this role.
• Coach the pod on continuous improvement, predictability, and self-organization under an agile delivery model that the client is actively adopting, not one already established.
• Maintain a working technical fluency in AI/GenAI delivery: LLMs, multi-agent systems, RAG pipelines, embeddings, vector databases, MLOps/LLMOps productionization challenges.
• Not required to build any of these but required to understand them well enough to engage credibly with the engineers on blockers, scope decisions, and prioritization trade-offs – and to earn their respect doing it.

Must Have Skills:

1. 8–10 years of Agile/Scrum leadership experience.
2. Resume must show sustained Scrum Master or Agile Delivery Lead roles – not occasional agile exposure within broader project management or BA work.
3. Demonstrated experience leading Agile teams in an AI, data engineering, or ML development environment. Standard software delivery experience without AI or data team context is not a substitute. 
4. Strong communication – business language and technical language, simultaneously.
5. This person presents to director level, translates between engineers and stakeholders, and writes user stories that bridge business intent and technical execution.
6. Proven ability to lead delivery in a rapid experimentation model where sprint outcomes are sometimes inconclusive.
7. Standard velocity-based delivery metrics do not apply cleanly to AI prototyping – candidates must demonstrate they understand the difference and have navigated it.

Nice to Have Skills:

1. Prior experience leading AI or GenAI initiatives – LLMs, RAG, agentic workflows. Explicitly called out by the hiring team on the spotlight call as a plus.
2. Energy sector or industrial domain experience.
3. Familiarity with pipeline operations context and terminology accelerates stakeholder translation in this environment.
4. PSM, CSM, SAFe, or equivalent Scrum/Agile certification.
5. Familiarity with MLOps and LLMOps productionization challenges – understanding the operationalization hurdles that AI practitioners face.
6. Experience translating complex AI workstreams into user stories for non-technical Product Owners and director-level stakeholders.
7. Experience standing up Agile practices within a non-agile enterprise culture – not just sustaining existing processes.

Job Location:

• Downtown Calgary, Alberta
• Hybrid Work Schedule (Mon/Tue/Thu in office)

WHAT SUCCESS LOOKS LIKE

• Senior Agile leadership with genuine hands-on experience in AI or data engineering team delivery is.
• Experience as a ‘Technical Delivery Lead’, ‘AI Product Manager’, and ‘Data Engineering Agile Lead’ channels – not from traditional Scrum Master or project management pipelines.
• The word ‘Agile’ as a search anchor will surface ceremony administrators.
• The word ‘delivery’ surfaces the practitioners you need.
• The non-negotiable is the combination of communication depth and AI environment experience.
• This person has to earn the respect of three senior technical practitioners within the first sprint.
• A polished Agile coach with no AI delivery context will be professionally tolerated and operationally ignored.