Data Scientist - Artificial Intelligence, Cloud & Automation

Leidos is seeking an AI Engineering Lead 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. You will lead AI engineering strategy and practices for L-CAP, integrating AI-augmented development tools, machine learning capabilities, and intelligent automation into the program’s engineering workflow. 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 position supports government programs and requires the ability to obtain and maintain a favorable Public Trust investigation.

This role is part of a growing program, and hiring will depend on available funding. We review applications on a rolling basis, but the timeline for interviews and offers may vary. In some cases, we may extend contingent offers that become active once funding is confirmed.

This position is located in Gaithersburg, MD; Egg Harbor Township, NJ; or Eagan, MN. This is an opportunity to contribute to projects that impact millions of air travelers.

This is a hybrid position requiring 3 days onsite and 2 days remote work. Candidates should reside a commutable distance to one of the above locations.

What You’ll Do

• Lead AI engineering strategy and roadmap development for the L-CAP program

• Design and implement MLOps pipelines for model development, training, and deployment

• Establish AI-augmented development practices across engineering teams

• Define model governance including versioning, monitoring, and lifecycle management

• Evaluate, pilot, and deploy AI development tools across the engineering organization

• Address safety considerations for AI applications in aviation-critical systems

• Drive intelligent automation initiatives to improve engineering productivity

• Integrate AI/ML capabilities with the L-CAP platform architecture

• Mentor engineering teams on AI/ML best practices and responsible AI principles

• Distinguish between AI capabilities that improve engineering productivity (developer tools, code generation, testing automation) and AI functionality incorporated into operational ATC services (decision support, anomaly detection, predictive maintenance)

• Define separate development practices, validation approaches, and certification considerations for engineering-productivity AI versus operational-mission AI

• Ensure alignment between requested AI skill sets and intended program objectives across both engineering and operational domains

• Champion an AI-first engineering culture by identifying and applying AI-assisted development capabilities, automation, and emerging software engineering practices that improve developer productivity, code quality, testing, and delivery., Linux Triage Ansible Parsing NetFlow Firewall Equities Webhooks Terraform Pipelines Leadership Automation Market Data RESTful API Shell Script Cyber Defense Change Control Cyber Security Virtualization Data Structures Network Routing Ancient History Machine Learning Network Topology Threat Detection Secret Clearance Traffic Analysis Network Protocols Elevation Drawings Prompt Engineering Workflow Management Linux Administration Network Infrastructure MITRE ATT&CK Framework Artificial Intelligence Infrastructure Security Bash (Scripting Language) Cyber Threat Intelligence IAT Level II Certification Cyber Kill Chain Framework CSSP Infrastructure Support Python (Programming Language) Snort (Intrusion Detection System) Puppet (Configuration Management Tool) Application Programming Interface (API) Security Information And Event Management (SIEM) Top Secret-Sensitive Compartmented Information (TS/SCI Clearance) +0

Google Cybersecurity Data Scientist - Artificial Intelligence, Cloud & Automation Leidos

Ft Meade, MD*On-Site

Planning Equities Timelines Terraform Hardening AI Agents Operations Leadership Management Automation Resilience Kubernetes Agentic AI Market Data Data Science Data Pipelines Microsoft Azure Law Enforcement Ancient History Machine Learning Cloud Operations Cyber Operations Support Services Computer Networks Cyber Engineering Workflow Management Amazon Web Services Technology Transfer GIAC Certifications SQL And Java (SQLJ) Software Development Operational Planning Intelligence Gathering Artificial Intelligence Certified Ethical Hacker Computer Network Defense IAT Level II Certification Infrastructure as Code (IaC) Python (Programming Language) GIAC Certified Incident Handler Artificial Intelligence Strategy Certified Information Systems Security Professional Top Secret-Sensitive Compartmented Information (TS/SCI Clearance) +0 AI Engineering Lead Leidos

Gaithersburg, MD*Remote

Tooling Equities Pipelines Leadership Management Automation Governance Kubernetes TensorFlow Reliability Market Data Low Latency Investigation ANSYS Meshing AWS SageMaker Systems Design Program Design Responsible AI Code Generation Computer Vision Ancient History Machine Learning Programming Tools Anomaly Detection Prompt Engineering Workflow Management Software Versioning Software Engineering Lifecycle Management Regulatory Compliance Predictive Maintenance Hybrid Cloud Computing Intelligent Automation Azure Machine Learning Air Traffic Management Artificial Intelligence Application Development Software Quality (SQA/SQC) Distributed Machine Learning Python (Programming Language) PyTorch (Machine Learning Library) MLOps (Machine Learning Operations) Artificial Intelligence Development Artificial Intelligence Infrastructure Applications Of Artificial Intelligence

Equities Pipelines Leadership Management Automation Governance Kubernetes TensorFlow Reliability Market Data Low Latency Investigation ANSYS Meshing AWS SageMaker Systems Design Program Design Responsible AI Code Generation Computer Vision Ancient History Machine Learning Programming Tools Anomaly Detection Prompt Engineering Workflow Management Software Versioning Software Engineering Lifecycle Management Regulatory Compliance Predictive Maintenance Hybrid Cloud Computing Intelligent Automation Azure Machine Learning Air Traffic Management Artificial Intelligence Application Development Software Quality (SQA/SQC) Distributed Machine Learning Python (Programming Language), * Bachelor’s degree with 8+ years of AI/ML engineering experience (Master’s preferred)

• ML/AI engineering leadership including team and strategy management

• MLOps pipeline design and implementation at enterprise scale

• Strong Python expertise and ML framework proficiency (PyTorch, TensorFlow)

• Model deployment, monitoring, and lifecycle management

• Experience with AI-assisted development tools and productivity platforms

• Large-scale ML system design and distributed training

• Engineering automation and intelligent workflow design

• Cloud ML services experience (AWS SageMaker, Azure ML, or equivalent)
• 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

• Aviation or safety-critical AI/ML application experience

• Responsible AI frameworks and governance implementation

• LLM integration and prompt engineering for enterprise applications

• Computer vision or NLP application development

• Real-time inference and low-latency ML serving

• Kubernetes-based ML workload orchestration

• AI governance and regulatory compliance frameworks

• Experience differentiating AI/ML development pipelines for internal tooling versus safety-critical operational systems

• Knowledge of certification requirements for AI systems in aviation or safety-critical operational environments

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.

Pay and benefits are fundamental to any career decision. That’s why we craft compensation packages that reflect the importance of the work we do for our customers. Employment benefits include competitive compensation, Health and Wellness programs, Income Protection, Paid Leave and Retirement. More details are available at www.leidos.com/careers/pay-benefits .

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., Leidos is an industry and technology leader serving government and commercial customers with smarter, more efficient digital and mission innovations. Headquartered in Reston, Virginia, with 47,000 global employees, Leidos reported annual revenues of approximately $16.7 billion for the fiscal year ended January 3, 2025. For more information, visit www.Leidos.com .