Director of AI Engineering, Cover Whale

• Seasoned engineering leadership with a thorough understanding of agentic workflows as they relate to agentic software engineering
• Deep understanding of CI/CD, quality assurance automation, and deployment integrity in high-velocity environments
• Track record of leading engineering teams through significant technology or process transformations
• Ability to architect trust and permission models for systems where automated agents produce production artifacts
• Competencies:
• Complexity of Work: Grasps the complexity of work items communicated by any level of engineer. Expertly supports the team and drives the priority of engineering work
• Judgment & Decision-Making: Leverages deep management experience to bring maturity and thoughtfulness to decisions. Elevates collective judgment across the engineering department
• Leadership: Balances leadership and management. Creates own work, mentors managers and engineers, and contributes to continuous improvement of the department
• Communication: Communicates complex technical topics concisely to direct reports, peers, and senior leadership. Frames technical matters against business needs
• Toolbox: Stays current with tools and evolving technologies. Drives strategic conversations by aligning technical concepts with business value. Stewards the company's finances by aligning team needs with budget
• Expertise : Applies breadth of knowledge across operational initiatives. Ensures alignment among direct reports and manages information flow between departments
• Core Values: Embodies Cover Whale's core values publicly and drives conversations to ensure managers convey these values to their teams.:

Desirable

• We are looking for a player-coach: hands-on building the platform while also leading and developing the engineering team
• Your Mandate is to ensure that humans and AI agents collaborate safely, reliably, and at velocity
• This is not a rebranded Director of Engineering. It is a new position, purpose-built for a new way of building software
• Cover Whale is operating an agentic engineering model where pods of product managers, engineers, and AI agents deliver production software together
• The Director of AI Platform Engineering owns the platform those pods operate on — the agent orchestration layer, trust boundaries, human-in-the-loop controls, and evaluation pipelines that make it safe and effective to delegate work to AI at production scale
• Agentic Platform Architecture Human-in-the-loop boundaries — setting trust thresholds where AI-generated output is auto-approved versus escalated for review
• Prompt and spec evaluation pipelines — the systems that validate whether AI-generated code, tests, and configurations meet production standards before reaching a human reviewer
• The end-to-end specification-through-deployment pipeline: how specs become agent instructions and how agent output becomes production code
• Evaluation and integration of emerging AI tooling, models, and agent frameworks
• Quality gates calibrated for AI-augmented velocity — ensuring AI-generated output meets production standards
• Engineering standards: branch protection, test coverage, CI/CD rules, and deployment integrity
• Architectural escalation path for engineers facing technical blockers
• Collaboration with the Technical Program Leader on engineering flow patterns and systemic bottlenecks
• Coaching engineers through the identity shift from "I write code" to "I orchestrate AI agents and own outcomes"
• Career development, performance accountability, and 1:1s — with expectations calibrated to the expanded role of delegate, review, and own
• Building team culture where engineers treat AI agents as force multipliers, not threats