You love turning real business problems into
working AI solutions - and you're not afraid to roll up your sleeves to ship them. In this role,
you'll lead Diligent's internal AI Solutions function, a small, high-impact team that is
embedding AI and GenAI into the systems thousands of colleagues use every day across Marketing, Sales, Customer Success, Finance, HR, Legal, and Product & Engineering.
You'll
set the AI vision and roadmap for internal tools, architect solutions, and still
build hands-on - from prototypes and reference implementations through to
production-grade integrations. You'll own how AI shows up inside ERP, CRM, BI and core IT platforms, and you'll be accountable for making those solutions reliable, secure, compliant, and measurably valuable for the business.
If you enjoy being a
"player-coach" who can move seamlessly between executive conversations and deep technical reviews, this role gives you the scope, visibility, and impact to shape how a global SaaS leader uses AI to run smarter and faster.
Here's a breakdown of what you'll do (not all of it, just the important stuff)- Lead, coach, and grow a high-performing team of AI Solutions Architects and Engineers, setting clear goals and building the capabilities the business needs as AI demand scales.
- Define and own the strategy, vision, and roadmap for internal AI solutions, translating business priorities into a focused portfolio of AI and platform initiatives.
- Design and deliver end-to-end AI/GenAI solutions - from ideation and prototyping through production deployment, monitoring, and continuous improvement.
- Embed AI capabilities (such as RAG, copilots, agents, summarization, and classification) into core business applications including ERP, CRM, BI, and other enterprise systems in a robust, maintainable way.
- Act as a trusted advisor to senior and executive stakeholders, turning technical possibilities into clear business value and measurable KPIs and ROI for AI initiatives.
- Champion responsible AI, governance, and security - ensuring privacy, fairness, and regulatory compliance, and driving AI and data literacy through enablement, documentation, and workshops.
These are the essentials you'll need to get an interview - Proven "player-coach" experience: you still build hands-on (coding, standing up prototypes/reference implementations, unblocking hard problems) rather than managing AI delivery from a distance.
- Track record of building, leading, and developing technical teams, including hiring, performance management, capability planning, and career development.
- Deep, current AI/GenAI expertise with LLMs, RAG, agents/workflows, prompt engineering, and evaluation, with enough technical depth to review designs and make sound architecture trade-offs.
- Strong background in IT platform engineering for enterprise tools such as the Atlassian suite and Microsoft 365/Azure (or comparable), including configuration, integration, automation, lifecycle management, and ownership of reliability and security.
- Hands-on experience integrating AI into core business platforms (for example Salesforce/CRM, ERP, BI) via APIs and cloud infrastructure (AWS preferred), with solutions running successfully in production.
- Proven ability to own strategy, roadmap, and portfolio for AI and platforms - sequencing initiatives and allocating team capacity across competing demands.
- Confidence working with senior business and IT leaders, including accountability for KPIs/ROI and for responsible AI, security, and compliance across everything shipped.
It would be great if you had these too, but we'll support you if you don't - Experience building or scaling an internal AI or AI enablement function in a global SaaS or large enterprise environment, ideally operating across multiple regions and time zones.
- Familiarity with MLOps/LLMOps practices (model lifecycle, experiment tracking, evaluation, drift monitoring) and modern engineering practices such as containerization and CI/CD.
- Exposure to classical machine learning and analytics (for example Scikit-learn, dashboards) and the ability to collaborate effectively with data and ML teams.
Pay Range
$131,000-$164,000 CAD
Headquartered in New York, Diligent has offices in Washington D.C., London, Galway, Budapest, Vancouver, Bengaluru, Munich, Singapore and Sydney. To foster strong collaboration and connection, this role will follow a hybrid work model. If you are within a commuting distance to one of our Diligent office locations, you will be expected to
work onsite at least 50% of the time. We believe that in-person engagement helps drive innovation, teamwork, and a strong sense of community.
