Senior Director, AI Software Engineering - Diligent Corporation

Overview

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.

What You’ll Do

Lead AI Engineering Across GRC

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

Stay Hands-On

• 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

Build and Scale Teams

• 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

Drive Execution

• Deliver production-grade systems—not experiments
• Balance speed with rigor (security, privacy, compliance)
• Operate across multiple concurrent initiatives with clear prioritization

Communicate and Influence

• 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

What We’re Looking For

Proven Builder

• 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)

Technical Depth

• 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)

Leadership with Credibility

• Experience leading engineering teams while remaining technically engaged
• Ability to earn trust with senior engineers and challenge them constructively

Strong Communicator

• Can simplify complex technical concepts for non-technical stakeholders