AI Account Director
Sales - Toronto, Ontario (Hybrid)
A technology innovation firm that has launched 750+
applications over the past 18 years for global brands including Suncor, Loblaw,
Petro Canada, RBC, Porter Airlines, Chatters, David Yurman, Meridian, Empire
Life, First Canadian Title, Gateway Casinos, and the Canadian Standards
Association.
We bridge the gap between AI's promise and business reality, delivering pragmatic AI solutions that create measurable business outcomes rather than theoretical possibilities. Our approach is business-first: we start with client objectives and work backward to ensure every AI initiative delivers measurable ROI. We are looking for builders who share this philosophy.
Our work increasingly takes us beyond individual AI use
cases into designing enterprise agentic frameworks - the
orchestration, observation, and decision-modelling layers that unify our
clients' existing AI platforms into coherent, governable, brand-safe systems.
We are connected into the Canada AI Alliance and Global AI Leaders Alliance
networks, giving us cross-industry visibility into how the most demanding AI
organizations are building.
Role Summary
- AI
consulting sales to enterprise accounts
- find
the wedge, run the pursuit, close the work, and grow the account after
delivery starts.
- Consultative
sales
They sell AI advisory and implementation into retail and grocery, financial services, manufacturing, automotive, and healthcare sectors. Buyers are executives who are past the pilot stage and want business outcomes, not model demos.
What you own
- Run
client Discovery calls & Discovery wedges - AI use case
demos, AI-DLC framework workshop, agentic framework workshop, AI ROI
calculator wedge, AI Talent playbook wedge, AI adoption playbooks wedge
etc
- Pursuit
management. Run the deal: qualification, stakeholder mapping,
pursuit plan, timelines, internal resourcing.
- Solution
shaping. Frame the client problem and the commercial case. Our AI
and consulting leads design the solution; you own the narrative, the value
case, and the fit.
- Proposals
and RFPs. Own the proposal and its commercial structure,
including pricing and scope trade-offs.
- Negotiation
and close. Carry the number. Own MSAs, SOWs, and renewal
negotiations through to signature.
- Client
partnership. Be the client's senior point of contact after
signature. Protect delivery quality, surface issues early, and stay in the
account.
- Account
growth. Mine and farm the accounts you close. Expand from the
first engagement into adjacent business units and use cases.
What you need
- 8+
years selling enterprise technology services, with a track record of
closing multi-million-dollar engagements into executive buyers.
- A
consulting or professional-services background. You can hold a business
conversation about operations, margin, and risk before anyone opens a
slide.
- Fluency
in AI: what agentic systems actually do, where they fail, and how
enterprises govern them. You do not need to build them.
- AI-native
working habits. You use these tools daily in your own work - research,
account planning, proposal drafting, follow-up.
- Comfort
as the senior person in the room with a CIO, COO, or divisional GM.
Strong Assets
- Existing
relationships in one or more of our target sectors.
- Demo
delivery - you can run a working demo yourself rather than scheduling one.
- RFP
and proposal writing strength.
- Partner-led
selling through hyperscalers or systems integrators.
How Performance in measured
- Annual
booked revenue against quota.
- Qualified
pipeline generated, self-sourced share.
- Win
rate and average engagement size.
- Account
expansion: revenue growth in year two of an account versus year one.
- Client
retention and reference quality.
What You Will Work On
They deliver solutions across several domains. Here are
examples of the types of projects you would contribute to:
- Designing
the cross-platform agentic framework - orchestration, observation, and
decision modelling - for an enterprise client unifying Salesforce
Agentforce, Snowflake Cortex, Sigma, and Enterprise ChatGPT into a single
governable system.
- Building
multi-agent systems that reduce manual decision-making by 30% and improve
response times by 40%.
- Implementing
AI-driven quality monitoring for manufacturing clients that reduces batch
rejections by 25%.
- Developing
hyper-personalization engines for retail and luxury clients that increase
digital conversion rates by 20–27%.
- Creating
data pipelines and AI infrastructure that enable new AI initiatives while
reducing data preparation time by 60%.
- Architecting
observability, evaluation, and governance frameworks that pass enterprise
brand, legal, and privacy review.
- Building
reference architectures and reusable IP that scale across multiple
engagements.
