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Salary
$70k – $126k per year
Location
Hybrid (Gaithersburg, United States)
Visa
H-1B filings in 12 months: 50 · for this role: 22 · green card filings: 24
Employment
Full-Time

Confirmed on the employer's own hiring board on Oct 17, 2026. First seen by Alion on Oct 16, 2026. Leidos scores B on the Alion truth index.

Overview
Company
Impact
Profile match
Leidos is an American technology and engineering services company created in 2013 when Science Applications International Corporation split in two, with Leidos taking the technical services and solutions business. It is one of the largest suppliers to the United States government, working across defence programmes, intelligence systems, civil agencies including the Federal Aviation Administration, and healthcare services for the Department of Veterans Affairs. Headquartered in Reston, Virginia, the company also builds security detection products for airports and borders, and has concentrated recent investment on trusted artificial intelligence and autonomy for mission environments.

Leidos is seeking an AI Software Developer to join the Air Traffic Business Area within the Homeland Sector supporting the development of the Leidos Common Automation Platform (L-CAP). L-CAP is a mission-critical, future-ready automation platform built on a hybrid cloud data mesh architecture, enabling next-generation air traffic management capabilities. We are building with an AI-first engineering mindset, embracing emerging AI capabilities and modern development practices to accelerate delivery, improve software quality, and continuously evolve how we design and build mission-critical systems. This role operates within a SAFe/Agile framework as part of an Agile Release Train (ART) delivering iterative value across the program.

In this position, you will design and implement software solutions independently while working closely with systems engineering, product delivery, and DevSecOps teams. The primary focus is on developing 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

This is a hybrid position requiring 3 days onsite and 2 days working from home, i f you are located within a commutable distance (Less than 1 hour's drive one-way during normal traffic) from Gaithersburg, MD; Eagan, MN; or Egg Harbor Township, NJ. However, if you do not reside within a commutable distance, you may be considered for a 100% remote role.

This role focuses on building and modernizing real-time, safety-critical systems using a combination of traditional systems engineering and AI-augmented software development practices. You’ll work on software that directly supports national air traffic operations, applying AI tools to accelerate development, improve quality, and enhance system reliability.

What You’ll Do

  • 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.

Core Technical Qualifications:

  • 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 below.
  • Experience AND knowledge will drive level:
    • 2 or more years
  • 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
  • Ability to obtain and maintain a Public Trust
  • U.S. citizenship required
  • Successful completion of background investigations as required by the government customer

Preferred / Desired Qualifications

  • 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
  • Desired but not required: Commutable distance to Gaithersburg, MD; Eagan, MN; or Egg Harbor Township, NJ.

Why Leidos?

You’ll work on systems where performance, precision, and reliability matter - every second. This is not experimental AI for prototypes. This is disciplined, responsible AI applied to mission-critical software that supports national infrastructure.

If you’re excited by solving complex problems in regulated, real-world environments - and using AI as a force multiplier rather than a shortcut - we’d like to talk.

ATMC

If you're looking for comfort, keep scrolling. At Leidos, we outthink, outbuild, and outpace the status quo - because the mission demands it. We're not hiring followers. We're recruiting the ones who disrupt, provoke, and refuse to fail. Step 10 is ancient history. We're already at step 30 - and moving faster than anyone else dares.

Original Posting:

October 15, 2026

For U.S. Positions: While subject to change based on business needs, Leidos reasonably anticipates that this job requisition will remain open for at least 3 days with an anticipated close date of no earlier than 3 days after the original posting date as listed above.

Pay Range:

Pay Range $69,550.00 - $125,725.00

The Leidos pay range for this job level is a general guideline only and not a guarantee of compensation or salary. Additional factors considered in extending an offer include (but are not limited to) responsibilities of the job, education, experience, knowledge, skills, and abilities, as well as internal equity, alignment with market data, applicable bargaining agreement (if any), or other law.

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