Director, AI Software Engineering

Diligent Corporation•Vancouver, BC

10d•Hybrid

About The Position

We are seeking a hands-on Director of AI Software Engineering to lead and scale AI engineering efforts supporting multiple business units across Governance, Risk, and Compliance (GRC). This role sits at the intersection of product delivery, platform evolution, and applied AI—driving real-world impact across core workflows. This is not a pure management role. We are looking for a builder who leads from the front, someone who has recently written production code, shipped systems end-to-end, and can operate comfortably in ambiguity while aligning teams and stakeholders. 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. 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.

Requirements

10+ years in software engineering, with recent hands-on coding experience
Demonstrated track record of shipping production systems at scale
Experience with modern AI/ML systems (LLMs, NLP, search, or data platforms)
Strong backend engineering skills (e.g., Python, Java, or similar)
Experience with distributed systems, APIs, and cloud platforms (AWS/GCP/Azure)
Familiarity with modern AI stacks (e.g., vector search, embeddings, model serving, agent frameworks)
Experience leading engineering teams while remaining technically engaged
Ability to earn trust with senior engineers and challenge them constructively
Can simplify complex technical concepts for non-technical stakeholders
Comfortable operating at both executive and implementation levels
Bias for action; thrives in fast-moving, ambiguous environments
Focused on delivering measurable business impact—not just technical output

Nice To Haves

Experience in GRC, fintech, or regulated environments
Exposure to FedRAMP or similar compliance frameworks
Background in building AI-powered products (not just research)

Responsibilities

Own delivery of AI-powered capabilities embedded directly into business unit workflows (e.g., risk analysis, compliance automation, reporting, due diligence)
Partner with product, data, and platform teams to translate business problems into scalable AI systems
Contribute to architecture, code reviews, and critical path implementation
Prototype and validate new approaches (LLMs, agents, retrieval systems, classification pipelines, etc.)
Set engineering standards for performance, reliability, and cost efficiency
Lead and mentor a high-performing team of AI/ML and software engineers
Drive hiring, coaching, and career development
Establish a culture of ownership, speed, and technical excellence
Deliver production-grade systems—not experiments
Balance speed with rigor (security, privacy, compliance)
Operate across multiple concurrent initiatives with clear prioritization
Act as a bridge between engineering and business stakeholders
Clearly articulate trade-offs, risks, and outcomes to senior leadership
Align cross-functional teams around shared goals and timelines