AI Software Developer - All Levels Remote

Leidos•Egg Harbor Township, NJ

9d•$87,100 - $157,450•Hybrid

About The Position

Leidos is seeking AI Software Developers for Junior, Mid, and Senior levels to join the Air Traffic Business Area within the Homeland Sector. The role supports the development of the Leidos Common Automation Platform (L-CAP), a mission-critical, future-ready automation platform built on a hybrid cloud data mesh architecture for next-generation air traffic management. The team employs an AI-first engineering mindset, utilizing emerging AI capabilities and modern development practices. This position operates within a SAFe/Agile framework as part of an Agile Release Train (ART). The role involves designing and implementing software solutions, focusing on microservices-based applications within an Agile/SAFe environment. Experience with AI-enabled or data-driven systems is advantageous. This position supports government programs and requires the ability to obtain and maintain a favorable Public Trust investigation. The role focuses on building and modernizing real-time, safety-critical systems using traditional systems engineering and AI-augmented software development practices, applying AI tools to accelerate development, improve quality, and enhance system reliability for national air traffic operations.

Requirements

Bachelor’s degree in Computer Science, Engineering, or a related technical field (or equivalent experience in lieu of degree). A completed Master's degree will account for 2 additional years of experience.
2 or more years (Junior Level)
4 or more years (Mid Level)
8 or more years (Senior Level)
Proficiency in Java or C++ with demonstrated experience building production software
Experience designing and developing microservices-based applications
Strong understanding of RESTful API design and implementation
Experience with distributed systems and event-driven architectures
Proficiency with CI/CD pipelines and DevOps practices
Experience with relational databases (PostgreSQL, Oracle) and NoSQL databases (MongoDB, Cassandra)
Solid experience with Git and collaborative development workflows
Familiarity with Agile/SAFe frameworks and iterative delivery
Strong debugging, problem-solving, and analytical skills
Ability to obtain and maintain a Public Trust
Experience with performance engineering including profiling, benchmarking, and optimization of distributed services
Knowledge of interface stability practices and API versioning for service-based architectures
Experience modernizing legacy software into service-oriented or microservice implementations
U.S. citizenship required
Successful completion of background investigations as required by the government customer

Nice To Haves

Python programming proficiency
Experience with containerization and orchestration (Docker, Kubernetes)
Cloud platform experience (AWS, Azure) including managed services
Experience with message brokers (Kafka, RabbitMQ) and streaming architectures
Knowledge of domain-driven design and data mesh patterns
Experience in aviation, defense, or safety-critical software domains
Familiarity with infrastructure-as-code tools (Terraform, Ansible)
Experience with AI-assisted development tools (e.g., code generation, automated testing, intelligent debugging)
Experience with performance-critical distributed systems in operational or real-time environments
Commutable distance to Gaithersburg, MD; Eagan, MN; or Egg Harbor Township, NJ.

Responsibilities

Design and develop microservices that form the backbone of the L-CAP automation platform
Collaborate with architects to translate system designs into robust, scalable implementations
Implement RESTful APIs and event-driven integrations within a hybrid cloud data mesh architecture
Integrate with relational and NoSQL databases, ensuring data consistency and performance
Perform performance tuning and optimization of services operating in distributed environments
Conduct and lead code reviews, enforcing coding standards and best practices across the team
Mentor junior developers, providing technical guidance and supporting their professional growth
Troubleshoot and resolve complex issues spanning multiple services, APIs, and infrastructure layers
Contribute to technical documentation including design documents, API specifications, and runbooks
Participate actively in SAFe/Agile ceremonies and contribute to PI planning and backlog refinement
Perform performance engineering activities including profiling, optimization, and latency analysis for distributed ATC services
Maintain interface stability and backward compatibility when modernizing existing operational software into service-based implementations
Modernize legacy ATC automation functions into cloud-native service implementations preserving operational behavior and performance characteristics
Embrace an AI-first engineering culture by actively adopting AI-assisted development tools, automation, and modern engineering practices that improve productivity, code quality, and delivery velocity.