AI Native Software Developer

Leidos•Reston, VA

1d•Hybrid

About The Position

Leidos is seeking a junior-level AI Software Developer for the Airports, Borders, and Security Business Area within the Homeland Sector. The role supports development of 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, and DevSecOps teams. The work centers on microservices and real-time, mission-critical systems that support border and aviation security operations, including staffing allocation, checkpoint and lane management, passenger routing, exception management, communications, alerting, reporting, and predictive maintenance. The role also involves integrating diverse data feeds and predictive models, applying AI-assisted development tools, and maintaining system quality, reliability, privacy, and operational stability. The position is hybrid, with work in the Reston, Virginia office three days per week. Government-program support requires the ability to obtain and maintain a favorable Public Trust investigation, and U.S. citizenship is required.

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 (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 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.
SAFe, Kafka/event streaming, cloud (AWS/Azure/GCP), Docker/Kubernetes, CI/CD, and DevSecOps experience.
Stream processing experience with Apache Beam/Dataflow, Flink, or Spark, including windowing and handling out-of-order or late data.
Machine learning for tabular or time-series data, including gradient-boosted trees and quantile or survival models; model calibration/evaluation such as Brier, pinball loss, and 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, 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, and consent/retention; 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 (FAA SWIM, FIXM/AIXM, METAR/TAF) and simulation/queueing concepts.

Responsibilities

Design and build microservices supporting 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 that normalize diverse source schemas to a canonical event model.
Deliver features such as 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.