Lead Development Engineer -AI-Assisted Engineering

About the role

The Lead Development Engineer is a senior-level professional with advanced expertise across all skill dimensions. They lead and oversee complex projects, provide technical guidance and mentorship to teams, and drive the adoption of best practices and technologies across application development, testing, integration, data engineering, and infrastructure.

Responsibilities

• Design software, integration, data, and testing architecture; deliver high-complexity tasks across all skill dimensions as part of a team.
• Own the definition and continuous improvement of AI coding agent configurations, prompt libraries, and automated review standards for the organization.
• Design AI-assisted workflows that enable junior developers to deliver production-ready output across the entire stack; evaluate and select AI tools and platforms for the engineering organization.
• Drive adoption of AI-assisted development practices across teams; measure and report on AI-assisted development effectiveness and quality outcomes.
• Design, code, and debug applications in various software languages or tools; design software architecture as expert in multiple front-end and back-end frameworks.
• Develop software solutions by studying information needs, conferring with users, and studying systems flow, data usage, and work processes; establish and enforce coding standards, design patterns, and architecture principles.
• Design testing architecture for the enterprise; demonstrate expertise in automated testing frameworks integrated with Version Control, DevOps & CI/CD.
• Utilize chaos engineering to validate system resilience; develop and implement comprehensive test strategies and plans.
• Lead performance, load, and stress testing at enterprise scale; establish quality metrics and reporting frameworks for stakeholders and management.
• Design and oversee risk-based testing strategies across the organization.
• Design integration architecture for the enterprise; demonstrate expertise in designing and architecting integration solutions across systems and applications.

Qualifications

• Education: Bachelor’s, Master’s Degree, or a significant amount of relevant experience. Computer Science, Computer Engineering, Information Systems, Quantitative or Engineering Field preferred.
• Experience: 5+ years of relevant and practical experience.
• Special Skills: Programming (expert in multiple languages or software tools). Expert in multiple front-end and back-end frameworks. Expert in Data Engineering (pipelines, warehousing, streaming, governance, visualization) (preferred). Design patterns for Infrastructure as Code (IaC). Design patterns with Version Control, DevOps & CI/CD. Expert in automated testing; utilizes chaos engineering. Expert in APIs, Web Services, Middleware, Message Brokers, ETL (integration & data patterns preferred). Expert in Security (Authentication, Authorization, Encryption). Proficient in Monitoring and Alerting. Expert with Cloud Services (AWS, Azure, Google Cloud). Expert with Version Control (Git).