Director of AI Engineering
Cover Whale • United States
Posted: April 16, 2026
Job Description
About the Role
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.
You will be 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.
What You'll Own
- 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
Engineering System Integrity
- 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
People Leadership for an Agentic Team
- 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
What You Won't Own
- Product direction, spec writing, or feature prioritization (that's the product management team's role)
- Pod-level delivery — the pod is PM + Engineer + AI Agents; you govern the platform they operate on
- Company-wide AI enablement and adoption (that's the AI Enablement Lead
Required
- 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
Preferred
- Hands-on experience with Anthropic toolsets such as Claude Code and associated Claude tooling
- Background in insurtech, fintech, or other regulated industries where compliance and security oversight are table stakes
- Experience implementing evaluation and observability pipelines for AI-generated output
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.
Additional Content
About the Role
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.
You will be 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.
What You'll Own
- 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
Engineering System Integrity
- 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
People Leadership for an Agentic Team
- 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
What You Won't Own
- Product direction, spec writing, or feature prioritization (that's the product management team's role)
- Pod-level delivery — the pod is PM + Engineer + AI Agents; you govern the platform they operate on
- Company-wide AI enablement and adoption (that's the AI Enablement Lead
Required
- 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
Preferred
- Hands-on experience with Anthropic toolsets such as Claude Code and associated Claude tooling
- Background in insurtech, fintech, or other regulated industries where compliance and security oversight are table stakes
- Experience implementing evaluation and observability pipelines for AI-generated output
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.