Job Details:
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. They establish (not just follow) the software product engineering best practices for the organization and are responsible for encoding those standards into AI coding agents at scale. This position consolidates responsibilities formerly held by the specialized Lead Development Engineer, Lead Integration Engineer, Lead Quality Engineer, and Lead IT Data Engineer roles.
Essential Duties and 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.
(Preferred / Nice-to-Have)
Expert in APIs and Web Services (RESTful, SOAP, gRPC), middleware and message brokers, ETL processes; expert in integration platforms and tools (SnapLogic, MuleSoft, Dell Boomi, Apache Camel, Talend). (Preferred / Nice-to-Have) Lead the resolution of complex integration escalations; drive preventive measures. (Preferred / Nice-to-Have) Help drive overall data strategy including designing and implementing comprehensive data architectures and visualization solutions; architect end-to-end data solutions with strong emphasis on cloud cost optimization. (Preferred / Nice-to-Have) Drive data strategy alignment with organizational goals; ensure enterprise-level data governance and security including advanced protections. (Preferred / Nice-to-Have) Lead integration of big data technologies, data streaming solutions, and advanced visualization tools in large-scale environments; oversee complex data pipeline orchestration. (Preferred / Nice-to-Have) Mentor engineers in SQL, scripting, and advanced data visualization techniques. (Preferred / Nice-to-Have) Expert in Infrastructure as Code (IaC); design patterns for cloud infrastructure management. Expert in DevOps and CI/CD (Jenkins, GitLab CI, CircleCI, or equivalent); establish organizational pipeline standards. Expert in Security (Authentication, Authorization, Encryption); design security architecture. Expert in Monitoring and Alerting (Splunk, ELK Stack, or equivalent); design observability strategy; lead cloud cost optimization and resource management. Lead and influence in collaborative meetings with peers and stakeholders; lead interactions with stakeholders to create requirements and demonstrate work. Document code, architecture, integration processes, APIs, and outcomes; establish software product engineering best practices across all skill dimensions. Review and correct others. Scope: Enterprise. Work independently with limited supervision; act as a knowledge resource within the team; lead and define priorities for projects or processes. Apply judgment and experience to identify resolution; make timely decisions and take action. Perform other assigned job-related duties that align with our organization's vision, mission, and values and fall within your scope of practice.
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). AI agent architecture, prompt engineering, and AI-assisted SDLC design. Technical Writing and Diagramming. Analysis (Technical, Business, or Data).
Soft Skills
Leadership: Driving engineering strategy and best practices across the organization; providing technical guidance and mentorship. Stakeholder Management: Building and maintaining relationships with internal and external partners. Strategic Vision: Aligning engineering initiatives with long-term business objectives. Communication: Presenting complex technical concepts to executive leadership. Mentorship: Fostering the growth and development of the engineering team across all skill dimensions. Decision-Making: Making informed choices about architecture, tools, and AI adoption. Change Management: Guiding the organization through engineering transformations and the shift to AI-assisted development. Emotional Intelligence: Understanding and motivating team members.
**Not eligible for visa sponsorship now or in the future**
**Not eligible for relocation assistance**
Relocation Assistance Eligible:
No
Work Shift:
1ST SHIFT (United States of America)
