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SG
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Diligent

Senior Manager, BT Applications

Vancouver, BC, Canada

$131,440.00-$180,730.00 · Full-time

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Job details

Pay: $131,440.00-$180,730.00
Job type: Full-time
Apply by: Nov 26, 2026
Posting language: English
Posted: Oct 27, 2026

Original job description

Diligent is the AI leader in governance, risk and compliance (GRC) SaaS solutions, helping more than 1 million users and 700,000 board members to clarify risk and elevate governance. The Diligent One Platform gives practitioners, the C-Suite and the board a consolidated view of their entire GRC practice so they can more effectively manage risk, build greater resilience and make better decisions, faster.

At Diligent, we're building the future with people who think boldly and move fast. Whether you're designing systems that leverage large language models or part of a team reimaging workflows with AI, you'll help us unlock entirely new ways of working and thinking. Curiosity is in our DNA, we look for individuals willing to ask the big questions and experiment fearlessly - those who embrace change not as a challenge, but as an opportunity. The future belongs to those who keep learning, and we are building it together. At Diligent, you’re not just building the future - you’re an agent of positive change, joining a global community on a mission to make an impact.

A Day in the Life

The Senior Manager, BT Applications will lead multiple Business Systems and applications teams in delivering high-quality technology solutions for our internal stakeholders. In this role, you will own a portfolio of enterprise applications and projects, partnering with senior leaders across Finance, Sales, and other functions to prioritize demand, shape roadmaps, and ensure predictable, high-quality delivery. You will provide both people leadership and strategic guidance, overseeing solution design, process optimization, and continuous improvement in how we analyse, build, test, and support our core systems. This position is ideal for a hands-on leader who combines deep enterprise applications experience with strong stakeholder management, coaching, and change-leadership skills.

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 you’ll lead Diligent’s internal AI Solutions function, a small, high-impact team that is embedding AI and GenA 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 reference implementations through to production-grade integrations build hands-on - from prototypes and 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 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 2 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 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.

What Diligent Offers You

Pay Range

$131,440.00-$180,730.00

Incentive Compensation

Offers will be negotiated based on each candidate's qualifications.

This role is eligible to participate in our annual incentive plan. Incentives are earned based on employee performance against defined metrics and company goals.

Benefits

Full-time roles are eligible for our comprehensive benefits program which includes medical, dental and vision coverage. You may also contribute to our 401(k) plan that includes a company match.

Creativity is ingrained in our culture. We are innovative collaborators by nature. We thrive in exploring how things can be differently both in our internal processes and to help our clients. We care about our people. Diligent offers a flexible work environment, global days of service, comprehensive health benefits, meeting free days, generous time off policy and wellness programs. (among others) Diversity is important to us. Growing, maintaining and promoting a diverse team is a top priority for us. We foster and encourage diversity through our Employee Resource Groups and provide access to resources and education to support the education of our team, facilitate dialogue, and foster understanding.

Diligent created the modern governance movement. Our world-changing idea is to empower leaders with the technology, insights and connections they need to drive greater impact and accountability – to lead with purpose. Our employees are passionate, smart, and creative people who not only want to help build the software company of the future, but who want to make the world a more sustainable, equitable and better place.

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.

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More about this job

Responsibilities

Lead and develop the AI Solutions team while setting the strategy and roadmap for internal AI initiatives across enterprise applications such as ERP, CRM, BI, and core IT platforms. Design and deliver production-ready AI solutions, advise senior stakeholders on business value and KPIs, and ensure solutions are reliable, secure, compliant, and continuously improved.

Requirements

Candidates need hands-on experience building and deploying AI/GenAI solutions, deep expertise in LLMs, RAG, agents, prompt engineering, and evaluation, and a record of leading technical teams. They should also have enterprise platform engineering and integration experience, portfolio ownership, and the ability to work with senior leaders on ROI, security, and responsible AI.

Skills

AI And Generative AI
Large Language Models
Retrieval-Augmented Generation
AI Agents And Workflows
Prompt Engineering
AI Evaluation
Enterprise Application Integration
IT Platform Engineering
Solution Architecture
People Leadership
Roadmap And Portfolio Management
Stakeholder Management
Responsible AI Governance
Security And Compliance
MLOps And LLMOps
CI/CD

Benefits

Medical Coverage
Dental Coverage
Vision Coverage
401(k) With Company Match
Flexible Work Environment
Global Days Of Service
Meeting-Free Days
Paid Time Off
Wellness Programs

Visa sponsorship

Not detected in the job text

Keywords

Artificial Intelligence
Generative AI
Large Language Models
Retrieval-Augmented Generation
AI Agents
Copilots
Prompt Engineering
AI Evaluation
ERP
CRM
Salesforce
Business Intelligence
Atlassian Suite
Microsoft 365
Azure
AWS
APIs
Cloud Infrastructure
MLOps
LLMOps
Model Lifecycle Management
Experiment Tracking
Drift Monitoring
Containerization
CI/CD
Scikit-Learn
Responsible AI
AI Governance
Data Literacy
Enterprise Applications

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