Senior Applications Engineer

Senior Applications Engineer Join a team where innovation meets mission. Our AI, cloud, cyber, and modernization solutions save agencies thousands of hours, safeguard national security, and strengthen health and humanitarian missions worldwide. With more than 1,700+ team members, 1,500+ AI & data experts, and 100+ prime contracts, we deliver at scale and with purpose. We've been recognized as a Top Workplace by The Washington Post for six consecutive years and named to the Inc. 5000 list of Fastest-Growing Private Companies in 13 of the past 14 years. Credence is a welcoming environment for those looking to grow and make a meaningful impact. We encourage employees to push boundaries and help solve critical, world-changing federal challenges. Credence has an immediate opening for a Senior Applications Engineer who will be primarily responsible for supporting the Defense Logistics Agency, Defense Automated Addressing Systems (DAAS), AI/ML program. The Senior Applications Engineer analyzes and studies complex system requirements and leads the design and implementation of software tools and subsystems that support software reuse and domain analyses. This is a hands-on role that pairs deep applications engineering with front-end UI/UX development: you will be handed real enterprise applications with real user friction, and part of your mandate is to diagnose why users aren't engaging and rebuild experiences — interfaces, dashboards, and data visualizations surfacing AI/ML outputs — that they actually want to use. You will manage software development and support efforts using formal specifications, data flow diagrams, and other accepted design techniques and Computer-Aided Software Engineering (CASE) tools, while providing reliable cost and schedule estimates to program leadership. To succeed in this role, you should combine deep hands-on engineering expertise with modern front-end skills, the ability to guide development teams, improve existing systems, and enforce disciplined configuration management practices in support of DAAS AI/ML modernization efforts. Responsibilities include, but are not limited to the duties listed below: Front-End Engineering & UI/UXArchitecting and building performant, responsive, accessible (WCAG 2.1 AA) user interfaces using React/Next.js with TypeScript, HTML5, and CSS3Auditing existing applications to identify user adoption barriers through heuristic analysis, user research, and behavioral data, and translating insights into measurable improvements in engagement and task completion Designing and building interactive dashboards and data visualization layers (D3.js, Chart.js, or similar) that surface AI/ML outputs, analytics, and operational metrics to end users Developing reusable component libraries and design systems that scale across multiple products Leveraging AI coding assistants (e.g., GitHub Copilot, Cursor) as a productivity multiplier within disciplined, secure development workflows Technical Leadership & Delivery Mentoring junior developers on the project team, raising the front-end skill level across the program Analyzing and studying complex system requirements to inform software design and implementation decisions Designing software tools and subsystems to support software reuse and domain analyses, and managing their implementation Managing software development and support using formal specifications, data flow diagrams, other accepted design techniques, and Computer-Aided Software Engineering (CASE) tools Estimating software development costs and schedule, and communicating estimates and risks to program and project leadership Reviewing existing programs and assisting in making refinements, reducing operating time, and improving current techniques Supervising software configuration management, including version control, change control, and release integrity across the development lifecycle Contributing to code reviews, CI/CD pipelines (Jenkins, Git), artifact and dependency governance (Sonatype Nexus), and agile ceremonies (JIRA) Collaborating with cross-functional teams, developers, analysts, and stakeholders to deliver software solutions that meet or exceed client expectations Documenting and communicating the results of your effortsAI/ML Collaboration Collaborating with data engineers and ML teams to ensure AI/ML outputs are represented accurately and meaningfully in front-end dashboards and visualizations Developing working familiarity with the team's AI/ML tech stack sufficient to design effective interfaces around it (deep hands-on ML model development is not required — see Preferred Qualifications) Related duties or special projects as assigned