Jr AI Native Software Developer

Leidos is seeking a Jr level AI Software Developer to join the Airports Borders and Security (AB&S) Business Area within the Homeland Sector building the Travel & Customs Orchestration Platform a hybrid-cloud AI-driven system that senses data across the traveler journey (ATC data manifests border processing detection/security kiosks e-Gates staffing and capacity) predicts demand orchestrates resources and measures outcomes.

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 that power the platforms Sense Predict Orchestrate Measure operating model including the AI Detection Algorithm Marketplace used to evaluate and deploy third-party and in-house detection algorithms (prohibited items explosives weapons liquids novel threats behavioral indicators and future algorithm types). 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 role focuses on building and modernizing real-time mission-critical systems that directly support border and aviation security operations including dynamic staffing allocation checkpoint and lane management passenger routing exception management passenger communications cross-functional alerting performance reporting and predictive maintenance while applying AI tools to accelerate development improve quality and enhance system reliability. The platform serves stakeholders across the traveler journey including TSA CBP/ICE airport operators eu-LISA airlines Frontex ground handlers and passengers themselves.

**This is a Hybrid position; the candidate will be in the office (Reston VA) 3 days a week.

What Youll Do:

• Design and build microservices supporting the platforms Sense Predict Orchestrate Measure model
• Integrate real-time data feeds (ATC manifests border processing detection/security kiosks e-Gates) and contribute to the AI Detection Algorithm Marketplace
• Build and operate adapters/connectors that normalize diverse source schemas (e.g. FIXM/AIXM AODB airline feeds) to a canonical event model
• Deliver features like dynamic staffing allocation lane management passenger routing and predictive maintenance
• Develop calibrated predictive models (queue/wait connection-miss baggage crowding disruption propagation) and integrate LLM/RAG components for explanation and recommendation keeping generative AI off the numeric prediction path
• Work in an Agile/SAFe team with systems engineering DevSecOps and QA
• Implement privacy-by-design and zero-trust controls (tokenization policy-scoped access data minimization retention/expiry)
• Write clean tested code and use AI-assisted tools to speed development and improve quality
• Support troubleshooting performance tuning and continuous improvement to reduce wait times and increase throughput
• Implement modern automated testing strategies including unit integration contract end-to-end and deterministic replay/backtesting

Minimum Qualifications:

• BS/BA degree and 5 years related experience OR Masters with 2 years of related experience; 4 years of related experience in lieu of degree
• Ability to obtain/maintain Public Trust; U.S. citizenship is required
• Hands-on experience with microservices and at least one modern language (Java Python C)
• Experience with AI-assisted engineering tools and/or AI/ML-enabled systems
• Experience with event-driven / streaming architectures (e.g. Kafka Pub/Sub) and stream or batch data processing
• Experience building and consuming APIs (REST/gRPC OpenAPI/AsyncAPI) in distributed systems
• Experience enhancing and maintaining existing software systems while preserving operational stability
• Ability to navigate large complex distributed systems and translate them into higher-level architecture
• Agile experience; understanding of APIs and distributed systems

Preferred Qualifications:

• 1 year software development experience supporting a related industry border/aviation customer (TSA CBP/ICE eu-LISA Frontex airport operators airlines)
• SAFe Kafka/event streaming cloud (AWS/Azure/GCP) Docker/Kubernetes CI/CD and DevSecOps experience
• Stream processing (Apache Beam/Dataflow Flink or Spark) with windowing and out-of-order/late-data handling
• Machine learning for tabular/time-series data (gradient-boosted trees quantile/survival models) and model calibration/evaluation (Brier pinball loss AUC-PR)
• MLOps: feature stores model serving model registry and drift/skew monitoring (Vertex AI Kubeflow MLflow or Feast)
• LLM/RAG application development: embeddings vector search (e.g. pgvector/FAISS/Qdrant/Vertex Vector Search) and model-gateway design
• Infrastructure as Code (Terraform) and GCP-native services (GKE Cloud Run BigQuery Firestore/Redis)
• Zero-trust networking and privacy engineering (VPC/VPC-SC mTLS IAM tokenization consent/retention); familiarity with NIST 800-53 CMMC or FedRAMP/ATO
• Observability with OpenTelemetry (Cloud Logging/Monitoring/Trace or Grafana/Prometheus)
• TypeScript/React for operator/traveler/executive experiences and real-time data visualization
• Aviation/transport data standards (FAA SWIM FIXM/AIXM METAR/TAF) and simulation/queueing concepts

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

The Leidos pay range for this job level is a general guideline onlyand 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.