AI Native Software Developer
About The Position
Leidos is hiring a junior-level AI Software Developer in its Airports, Borders, and Security Business Area within the Homeland Sector. The position will build the Travel & Customs Orchestration Platform, a hybrid-cloud, AI-driven system that senses data across the traveler journey, predicts demand, orchestrates resources, and measures outcomes. The platform includes an AI Detection Algorithm Marketplace for evaluating and deploying third-party and in-house detection algorithms. The developer will design and implement software solutions independently while collaborating with systems engineering, product delivery, DevSecOps, and QA teams. The role focuses on microservices and real-time, mission-critical systems for border and aviation security, including staffing allocation, checkpoint and lane management, passenger routing, exception management, communications, alerting, reporting, and predictive maintenance. The position also applies AI tools to accelerate development and improve software quality and reliability. Government program support requires the ability to obtain and maintain a favorable Public Trust investigation; U.S. citizenship is required. This is a hybrid position with three days per week in the Reston, Virginia office.
Requirements
- Bachelor’s degree and 5 years of related experience, or a master’s degree and 2 years of related experience; 4 years of related experience may substitute for a degree.
- Ability to obtain and maintain a Public Trust investigation; U.S. citizenship is required.
- Hands-on experience with microservices and at least one modern programming language: Java, Python, or C++.
- Experience with AI-assisted engineering tools and/or AI/ML-enabled systems.
- Experience with event-driven or streaming architectures, such as Kafka or Pub/Sub, and stream or batch data processing.
- Experience building and consuming APIs, such as REST/gRPC and 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 and understanding of APIs and distributed systems.
Nice To Haves
- One year of software development experience supporting a related border or aviation industry customer, such as TSA, CBP/ICE, eu-LISA, Frontex, airport operators, or airlines.
- Experience with SAFe, Kafka/event streaming, cloud platforms (AWS/Azure/GCP), Docker/Kubernetes, CI/CD, and DevSecOps.
- Stream processing experience with Apache Beam/Dataflow, Flink, or Spark, including windowing and out-of-order or late-data handling.
- Machine learning for tabular or time-series data, including gradient-boosted trees, quantile/survival models, and model calibration/evaluation such as Brier, pinball loss, or AUC-PR.
- MLOps experience with feature stores, model serving, model registries, and drift/skew monitoring using tools such as Vertex AI, Kubeflow, MLflow, or Feast.
- LLM/RAG application development experience, including embeddings, vector search, and model-gateway design.
- Infrastructure as Code experience with Terraform and GCP-native services such as GKE, Cloud Run, BigQuery, and Firestore/Redis.
- Zero-trust networking and privacy engineering experience, including VPC/VPC-SC, mTLS, IAM, tokenization, consent/retention, and familiarity with NIST 800-53, CMMC, or FedRAMP/ATO.
- Observability experience with OpenTelemetry and Cloud Logging/Monitoring/Trace or Grafana/Prometheus.
- TypeScript/React experience for operator, traveler, or executive experiences and real-time data visualization.
- Knowledge of aviation/transport data standards such as FAA SWIM, FIXM/AIXM, or METAR/TAF, and simulation/queueing concepts.
Responsibilities
- Design and build microservices that support the platform’s Sense → Predict → Orchestrate → Measure model.
- Integrate real-time data feeds and contribute to the AI Detection Algorithm Marketplace.
- Build and operate adapters and connectors to normalize diverse source schemas into a canonical event model.
- Deliver features including dynamic staffing allocation, lane management, passenger routing, and predictive maintenance.
- Develop calibrated predictive models 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, including tokenization, policy-scoped access, data minimization, and retention/expiry.
- Write clean, tested code and use AI-assisted tools to accelerate development and improve quality.
- Support troubleshooting, performance tuning, and continuous improvement to reduce wait times and increase throughput.
- Implement automated testing strategies, including unit, integration, contract, end-to-end, and deterministic replay/backtesting.
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What This Job Offers
Job Type
Full-time
Career Level
Entry Level
