Confirmed on the employer's own hiring board on Oct 22, 2026. First seen by Alion on Sep 24, 2025. Meta scores B on the Alion truth index.
Responsibilities
Collaborate with cross-functional teams (product, design, operations, infrastructure) to build innovative application experiences Implement custom user interfaces using latest programming techniques and technologies Analyze and optimize code for quality, efficiency, and performance, and provide feedback to peers during code reviews Set direction and goals for teams, lead major initiatives, provide technical guidance and mentorship to peers, and help onboard new team members Architect efficient and scalable systems that drive complex applications Identify and resolve performance and scalability issues, and drive large efforts to reduce technical debt Work on a variety of coding languages and technologies Establish ownership of components, features, or systems with expert end-to-end understanding
Qualifications
8+ years of programming experience in a relevant programming language 6+ years relevant experience building large-scale applications or similar experience Experience leading major initiatives successfully. Experience leading projects and teams accordingly Experience building and shipping high quality work and achieving high reliability Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience Experience with scripting languages such as Python, Javascript or Hack Experience improving quality through thoughtful code reviews, appropriate testing, proper rollout, monitoring, and proactive changes Experienced in utilizing data and analysis to explain technical problems and providing detailed feedback and solutions Experience in programming languages such as C, C++, Java, Swift, or Kotlin Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements) Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews) Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies

