Lead Application Engineer
Lead Engineer, Enterprise ApplicationsWe 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 DevOps practices.Application Development & Technical LeadershipLead 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.Application Modernization & Portfolio ManagementAssess enterprise application portfolios to identify redundancy, technical debt, and opportunities for consolidation or and execute application rationalization strategies, including application retirement, consolidation, and migration to cloud or SaaS modernization initiatives involving microservices, API enablement, containerization, and legacy application AI-driven tools to analyze application portfolios and prioritize modernization opportunities to integrate AI services into legacy and modern applications to improve functionality and user experience.Engineering LeadershipManage 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, DevOps, and integration teams.Delivery Management & PerformanceTrack delivery metrics such as velocity, defect rates, deployment frequency, and cost progress, risks, technical debt reduction, and modernization ROI to stakeholders.Partner with product owners and business stakeholders to prioritize initiatives aligned with strategic objectives.Quality, Governance & DevOpsEnsure applications meet established standards for performance, security, accessibility, reliability, and scalability.Champion CI/CD, automated testing, observability, and DevOps 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.Cross-Functional Collaboration & Financial ManagementTranslate business requirements into scalable technical solutions and modernization roadmaps.Collaborate with internal teams, vendors, and technology partners supporting application development and transformation budgeting, forecasting, cost-benefit analysis, and resource use cases and roadmaps for incorporating AI capabilities into enterprise QualificationsBachelor'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 delivering customer-facing applications and leading enterprise application transformation proficiency with modern technology stacks such as JavaScript/TypeScript, 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 experience with Agile and DevOps technologies such as Jira, GitHub Actions, Jenkins, Terraform, or comparable with application portfolio management and 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 QualificationsPMP, AWS, TOGAF, or similar cloud, architecture, project management, or modernization with AI/ML platforms and services such as Azure AI, AWS AI/ML services, or comparable technologies.Experience building or integrating conversational AI, recommendation systems, or intelligent automation solutions.Key CompetenciesStrong leadership, team management, mentoring, and cross-functional collaboration skills.Strategic mindset with experience driving enterprise application modernization and communication skills with the ability to work effectively with technical teams, business stakeholders, and executive leadership.Data-driven approach to using KPIs to improve delivery, quality, and application portfolio performance.Ability to operate effectively in fast-paced, transformation-focused environments.Ability to identify and implement AI solutions that improve application functionality, engineering efficiency, and business outcomes.Understanding of responsible AI principles, including governance, explainability, privacy, and data security.