Lead Systems Engineer

Lead Systems EngineerThis position supports Revolutional's federal customer as part of an application transformation and modernization initiative. This program is driving a large-scale transformation of systems into a data-centric, cloud-native ecosystem capable of supporting high-volume, near real-time data processing and advanced analytics. The work includes modernization of legacy applications, development of new cloud-native solutions, and implementation of DevSecOps and scaled Agile practices across the organization. The core challenge: orchestrating complex, multi-contractor delivery while transforming both technology and operating models without disrupting mission-critical operations.As a Lead Systems Engineer at Revolutional, you will drive end-to-end systems engineering execution across a large-scale federal modernization program. You will operate between architecture and delivery—ensuring that system designs are translated into working, integrated, and scalable solutions. You will lead engineering efforts across multiple teams, coordinating system integration, requirements alignment, and technical execution. This role requires someone who can manage complexity across systems, enforce engineering discipline, and ensure delivery meets both technical and mission requirements.Responsibilities include providing technical leadership across systems engineering efforts within the DTAM program, translating architectural designs into actionable engineering plans and execution, defining and managing system requirements, interfaces, and integration points, leading system integration across applications, data platforms, and cloud environments, ensuring systems meet performance, scalability, reliability, and security requirements, identifying and resolving technical risks, dependencies, and integration challenges, supporting modernization efforts by engineering transitions from legacy to cloud-native systems, collaborating with architects, developers, data engineers, and program leadership to ensure alignment, driving adoption of DevSecOps practices, enabling automation, testing, and continuous delivery, participating in stakeholder discussions, providing technical insight and decision support, mentoring engineering teams and enforcing systems engineering best practices.Technical environment includes cloud-native transformation (AWS/Azure environments), high-volume, near real-time data processing systems, data-centric architectures and enterprise data ecosystems, DevSecOps pipelines and CI/CD practices, scaled Agile delivery models, legacy system modernization and refactoring.Baseline requirements include US citizenship with the ability to obtain a Public Trust, 15+ years of experience in systems engineering, integration, or technical leadership roles, proven experience supporting large-scale, complex IT systems or modernization programs, ability to obtain and maintain a Public Trust clearance.Technical capabilities include strong experience with systems engineering principles, including requirements, integration, and validation, experience integrating complex systems across applications, data platforms, and infrastructure, experience working in cloud-based environments and modern distributed systems, understanding of DevSecOps practices and system engineering within CI/CD environments, ability to manage system complexity across multiple teams and technical domains.Core strengths include strong ownership mindset with accountability for system-level outcomes, ability to translate complex technical designs into executable engineering plans, effective communication across technical teams and senior stakeholders, ability to operate in complex, fast-moving environments with multiple dependencies, strong problem-solving and decision-making capabilities with program-level impact.Nice to have include cloud certifications (AWS, Azure, or Google Cloud), Agile certifications (Scrum, SAFe, or similar), Certified Systems Engineering Professional (CSEP), experience supporting large-scale federal programs, experience with large-scale data systems or real-time processing environments.