Lead AI Software Developer

Responsibilities: of the Lead AI Software Developer: Participate in sprint planning, daily standups, reviews, and retrospectives Collaborate with systems engineering and program teams to translate requirements into working software solutions Develop clean, maintainable, and testable code following CI/CD and DevSecOps practices Contribute to system design discussions and technical decision-making Integrate services with databases, messaging systems, and external APIs Support troubleshooting, performance tuning, and continuous improvement Work closely with QA, DevOps, and platform teams to ensure reliable delivery Implement modern automated testing strategies, including unit, integration, contract, and end-to-end testing Use AI-assisted development tools to accelerate coding, refactoring, debugging, and test creation Qualification of the Lead AI Software Developer: Bachelor’s degree in Computer Science, Engineering, or a related technical field (or equivalent experience) 4+ years of relevant

Software Development, Artificial Intelligence (AI), Java, Test Strategy, Refactoring, Requirements Management, Sprint Planning, Artificial Intelligence (AI), Python Programming/Scripting Language, Test Suite, experience or a Master’s Degree and 2+ years of relevant experience Hands-on experience building and supporting microservices-based systems Proficiency in at least one modern programming language (e.g., Java, Python, C++, or similar on a Linux-based system) Effectively leverage AI-assisted engineering tools to understand unfamiliar codebases, analyze system behavior, develop implementation strategies, accelerate development, and improve software quality. Experience or exposure to AI/ML-enabled systems (Claude-Code), automation, or intelligent platforms. Ability to analyze and understand large, complex software systems with many interacting components. Analyze existing software interfaces and data flows to implement new capabilities within a complex distributed system. Experience enhancing and maintaining existing software systems while preserving operational stability. Ability to abstract complex implementation details into higher-level architectural concepts and communicate those concepts effectively. Experience working in Agile environments Understanding of APIs and distributed system concepts Ability to obtain and maintain a Public Trust Preferred Qualifications: Experience with large-scale distributed systems Experience working with safety-critical or high-availability software Experience reverse-engineering existing software designs Experience integrating with legacy systems Experience reading and understanding large existing codebases Experience with Git-based version control and CI/CD pipelines Familiarity with Scaled Agile Framework (SAFe) Experience working with relational and/or NoSQL databases Hands-on experience with Kafka or other event-streaming technologies Cloud experience (AWS, Azure, or GCP) Containerization and orchestration experience (Docker, Kubernetes) Experience working in DevSecOps environments Experience with test automation frameworks and integration of automated test suites into CI/CD pipelines Qualifications: : Experience with large-scale distributed systems Experience working with safety-critical or high-availability software Experience reverse-engineering existing software designs Experience integrating with legacy systems Experience reading and understanding large existing codebases Experience with Git-based version control and CI/CD pipelines Familiarity with Scaled Agile Framework (SAFe) Experience working with relational and/or NoSQL databases Hands-on experience with Kafka or other event-streaming technologies Cloud experience (AWS, Azure, or GCP) Containerization and orchestration experience (Docker, Kubernetes) Experience working in DevSecOps environments Experience with test automation frameworks and integration of automated test suites into CI/CD pipelines