Director, Software Engineering – Developer Platforms, AI

Role Overview

• Embed directly within product engineering teams to drive measurable improvements in developer productivity by integrating AI into daily workflow design, coding, testing, deployment, and operations
• Lead tool selection and adoption strategy for AI development platforms (GitHub Copilot, Claude Code, Cursor, etc.), establishing best practices for prompt engineering, context management, and workflow integration
• Build and maintain custom AI tooling, MCP servers, and integrations that provide teams with domain-specific context from your codebase, documentation, infrastructure, and business systems
• Develop and socialize reusable patterns for code generation, refactoring, test automation, incident analysis, and knowledge retrieval that teams can apply across their daily work
• Implement AI code review and validation practices to ensure AI-generated code meets security, quality, and HIPAA compliance standards
• Champion a culture of AI-augmented development that enables engineers to tackle bigger challenges, improve code quality, and reduce toil—without sacrificing maintainability or creating technical debt
• Create self-service documentation, learning paths, and enablement programs (workshops, office hours, communities of practice) to scale AI adoption across engineering
• Measure and communicate impact using both quantitative metrics (velocity, quality, time-to-deployment) and qualitative measures (developer satisfaction, cognitive load reduction, friction logging)
• Lead application-level infrastructure-as-code initiatives, empowering product teams to own their cloud resources (containers, SQS, Lambda, DocumentDB, DynamoDB, etc.)
• Design reference architectures and terraform/CDK patterns that balance team autonomy with consistency and security
• Partner with the enterprise DevOps team to establish clear boundaries—they own foundational infrastructure (VPCs, security groups, IAM foundations), you enable teams to own application-layer resources
• Build proof-of-concepts and migration playbooks as GHX transitions from lift-and-shift EC2 environments to truly cloud-native architectures
• Manage engineers on cloud-native design patterns, observability, cost optimization, and operational excellence
• Provide direction, hands-on execution to grow an engineering team
• Work closely with product managers, engineering leaders, and cross-functional partners to translate business needs into practical AI and infrastructure solutions
• Establish metrics and feedback loops to continuously improve both AI adoption and cloud-native maturity
• Balance innovation with pragmatism—championing new approaches while ensuring solutions scale sustainably.

Requirements

• 10+ years of software engineering experience with at least 3 years in technical leadership roles
• Deep hands-on experience with cloud-native architecture on AWS (containers/ECS/EKS, serverless, managed databases, event-driven patterns)
• Strong infrastructure-as-code background (Terraform, CloudFormation, or CDK) with experience enabling engineering teams to own their infrastructure
• Demonstrated experience integrating AI/LLM tools into software development workflows—whether through custom tooling, MCP servers, or commercial platforms (GitHub Copilot, Claude Code, Cursor, etc.)
• Track record of embedding with teams to drive technical transformation and measurable productivity improvements
• Excellent communication skills with ability to influence and mentor engineers across all levels
• Comfortable working in a player-coach capacity—rolling up sleeves while providing strategic direction.

Tech Stack

• AWS
• Cloud
• DynamoDB
• EC2
• Terraform

Benefits

• health, vision, and dental insurance
• accident and life insurance
• 401k matching
• paid-time off
• education reimbursement