Lead Development Engineer (Onsite)

Job Details:

Summary

The Lead Development Engineer is a senior-level professional with advanced expertise across all skill dimensions. The Lead Development Engineer is the premier technical expert within the immediate organization, responsible for defining the overarching architecture and establishing the strategic direction for application development, software quality, testing, data engineering, application support, and infrastructure automation. Working highly autonomously, they lead large-scale, complex projects and define the technical vision that teams execute. They evaluate new technologies – including standardizing AI coding agents across the organization, defining prompt patterns, and building automated review pipelines. This position consolidates responsibilities formerly held by the specialized Lead Development Engineer, Lead Integration Engineer, Lead Quality Engineer, IT Lead Data Engineer, and Lead IT Operations Analyst / Developer roles.

Essential Duties and Responsibilities

• Designs software, integration, data, and testing architecture. Delivers high-complexity tasks across all skill dimensions (Application Development, Testing, Integration, Data, Support, and Infra/DevOps).
• Leads and influences in collaborative meetings with peers and stakeholders. Leads interactions with stakeholders to create requirements and demonstrate work.
• Documents code, architecture, integration processes, APIs, and outcomes. Establishes software product engineering best practices across all skill dimensions. Reviews and corrects others. Scope: Enterprise.
• Owns the definition and continuous improvement of AI coding agent configurations, prompt libraries, and automated review standards for the organization.
• Works independently with limited supervision to perform work.
• Acts as a knowledge resource within the team. Leads and defines priorities for projects or processes.
• Applies judgment and experience to identify resolution. Ability to make timely decisions and to take action.
• Expected to be a productive leader by example of a team that designs and improves processes, procedures, and platforms.
• Performs other assigned job-related duties that align with our organization’s vision, mission, and values and fall within your scope of practice.

Application Development

• Designing, coding, and debugging applications in various software languages or tools.
• Designing software architecture; expert in multiple front-end and back-end frameworks.
• Developing software solutions by studying information needs, conferring with users, and studying systems flow, data usage, and work processes.
• Establishing and enforcing coding standards, design patterns, and architecture principles.
• Identify, build, and maintain reusable libraries or packages where appropriate, favoring shared solutions over duplication, and collaborate with peers to evolve common components.

Testing & Quality

• Designs testing architecture for the enterprise.
• Expert in automated testing frameworks integrated with Version Control, DevOps & CI/CD.
• Utilizes chaos engineering to validate system resilience.
• Developing and implementing comprehensive test strategies and plans.
• Leading enterprise-scale performance, load, and stress testing efforts; setting standards for performance benchmarking.
• Acting as the ultimate authority on software quality strategies and standards.

Application Support & Operations

• Defining organizational monitoring standards and frameworks.
• Managing enterprise support frameworks and leading critical incident resolution at an organizational level.
• Driving operational innovation by introducing new continuous improvement processes, automation, and technologies.
• Defining frameworks and auditing documentation quality and purpose across multiple systems.

Integration (Preferred / Nice-to-Have)

• Designs integration architecture for the enterprise.
• Expert in designing and architecting integration solutions across systems and applications.
• Expert in APIs and Web Services (e.g., RESTful, SOAP, gRPC, or organizational equivalent), middleware and message brokers, ETL processes.
• Expert in integration platforms and tools (e.g., SnapLogic, MuleSoft, Dell Boomi, Apache Camel, Talend, or organizational equivalent).
• Leading the resolution of complex integration escalations; driving preventive measures.

Data Engineering (Preferred / Nice-to-Have)

• Helps drive overall data strategy including designing and implementing comprehensive data architectures and visualization solutions.
• Architects end-to-end data solutions with strong emphasis on cloud cost optimization and enterprise-scale visualization.
• Drives data strategy alignment with organizational goals; contributes to strategic decision-making.
• Ensures enterprise-level data governance and security including advanced row-level and column-level protections.
• Leads integration of big data technologies, data streaming solutions, and advanced visualization tools in large-scale environments.
• Oversees complex data pipeline orchestration; drives adoption of cutting-edge ETL tools.
• Mentors engineers in SQL, scripting, and advanced data visualization techniques.

Infrastructure & DevOps

• Expert in Infrastructure as Code (IaC); designs patterns for cloud infrastructure management.
• Expert in DevOps and CI/CD (e.g., Jenkins, GitLab CI, CircleCI, or organizational equivalent); establishes organizational pipeline standards.
• Expert in Security (Authentication, Authorization, Encryption); designs security architecture.
• Expert in Monitoring and Alerting (e.g., Splunk, ELK Stack, or organizational equivalent); designs observability strategy.
• Leads cloud cost optimization and resource management.

AI-Assisted Engineering

• Owns and continuously improves the organization’s AI coding agent standards, prompt libraries, and automated review pipelines.
• Designs AI-assisted workflows that enable junior developers to deliver production-ready output across the entire stack.
• Evaluates and selects AI tools and platforms for the engineering organization.
• Drives adoption of AI-assisted development practices across teams.
• Measures and reports on AI-assisted development effectiveness and quality outcomes.
• Accountable for all work output, ensuring thorough review and validation of all AI-generated code, tests, and documentation.

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.

Technical 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 (e.g., AWS, Azure, Google Cloud, or organizational equivalent)
• Expert with Version Control (e.g., Git, or organizational equivalent)
• Designs and scales automated testing and CI/CD pipelines at an organizational level
• Advanced Application Support, Troubleshooting, and Root Cause Analysis
• 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.

Relocation Assistance Eligible:

No

Work Shift:

1ST SHIFT (United States of America)

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