Lead Application Engineer

Lead Engineer, Enterprise Applications

We are seeking a Lead Engineer, Enterprise Applications to lead the design, development, modernization, and lifecycle management of enterprise application portfolios. This role will oversee end-to-end application delivery, from requirements through production, while improving scalability, cost efficiency, reliability, and business agility.

The Lead Engineer will play a key role in application modernization, cloud adoption, application portfolio rationalization, AI enablement, and the implementation of modern engineering and Dev Ops practices.

• Lead end-to-end delivery of web, mobile, and cloud-native applications using modern frameworks and architectures.
• Define and govern technical architecture, development standards, and technology stack selection.
• Lead Agile development activities, including sprint planning, backlog refinement, and release management.
• Incorporate AI-assisted development tools, including code generation, automated testing, and documentation tools, to improve engineering productivity and quality.
• Evaluate and integrate AI/ML capabilities into applications, including intelligent workflows, predictive insights, and conversational interfaces.

• Assess enterprise application portfolios to identify redundancy, technical debt, and opportunities for consolidation or modernization.
• Develop and execute application rationalization strategies, including application retirement, consolidation, and migration to cloud or SaaS platforms.
• Lead modernization initiatives involving microservices, API enablement, containerization, and legacy application transformation.
• Utilize AI-driven tools to analyze application portfolios and prioritize modernization initiatives.
• Identify opportunities to integrate AI services into legacy and modern applications to improve functionality and user experience.

• Manage and allocate engineering resources based on skills, capacity, and strategic priorities.
• Mentor engineers, conduct code reviews, and promote modern software development and integration best practices.
• Foster collaboration across frontend, backend, Dev Ops, and integration teams.

• Track delivery metrics such as velocity, defect rates, deployment frequency, and cost optimization.
• Communicate progress, risks, technical debt reduction, and modernization ROI to stakeholders.
• Partner with product owners and business stakeholders to prioritize initiatives aligned with strategic objectives.

• Ensure applications meet established standards for performance, security, accessibility, reliability, and scalability.
• Champion CI/CD, automated testing, observability, and Dev Ops best practices.
• Participate in architecture governance, change management, and application portfolio oversight.
• Implement AI-enabled monitoring and observability solutions for anomaly detection, performance optimization, and incident prediction.
• Support responsible AI practices related to governance, data privacy, security, and enterprise compliance.

• Translate business requirements into scalable technical solutions and modernization roadmaps.
• Collaborate with internal teams, vendors, and technology partners supporting application development and transformation initiatives.
• Support budgeting, forecasting, cost-benefit analysis, and resource optimization.
• Define use cases and roadmaps for incorporating AI capabilities into enterprise applications.

• Bachelor's degree in Computer Science, Software Engineering, or a related field; master's degree preferred.
• 8+ years of software development experience, including 5+ years leading engineering teams and modernization initiatives.
• Experience delivering customer-facing applications and leading enterprise application transformation initiatives.
• Strong proficiency with modern technology stacks such as JavaScript/Type Script, React, Node.js, Java, .NET, Python, or similar technologies.
• Experience with cloud platforms such as AWS or Azure.
• Experience with Docker, Kubernetes, microservices architectures, and legacy application modernization.
• Hands-on experience with Agile and Dev Ops technologies such as Jira, Git Hub Actions, Jenkins, Terraform, or comparable platforms.
• Experience with application portfolio management and rationalization.
• Demonstrated ability to mentor engineers and scale engineering capabilities.
• Experience integrating AI/ML capabilities or APIs, including generative AI, NLP, predictive analytics, or similar technologies.
• Familiarity with AI-assisted software development tools.
• Understanding of data pipelines and integration patterns supporting AI-enabled applications.

• PMP, AWS, TOGAF, or similar cloud, architecture, project management, or modernization certifications.
• Experience with AI/ML platforms and services such as Azure AI, AWS…