AI Native Software Developer

Leidos•Reston, VA

2d•Hybrid

About The Position

Leidos is seeking a junior-level AI Software Developer for the Airports, Borders, and Security (AB&S) 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 independently design and implement software solutions while collaborating with systems engineering, product delivery, DevSecOps, and QA teams. The work involves building and modernizing real-time, mission-critical systems for border and aviation security, including staffing allocation, checkpoint and lane management, passenger routing and communications, exception management, cross-functional alerting, performance reporting, and predictive maintenance. The role also applies AI tools to accelerate development and improve quality and system reliability. Experience with AI-enabled or data-driven systems is advantageous. The position supports government programs and requires the ability to obtain and maintain a favorable Public Trust investigation. U.S. citizenship is required. This is a hybrid role based in Reston, Virginia, with three days per week in the office.

Requirements

Bachelor’s degree and 4 years of related experience, or a master’s degree and 2 years of related experience; 4 years of related experience may be substituted 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, 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 experience with tabular or time-series data, including gradient-boosted trees, quantile or survival models, and model calibration/evaluation such as Brier score, pinball loss, or AUC-PR.
MLOps experience with feature stores, model serving, model registries, and drift/skew monitoring using 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.
Familiarity with aviation/transport data standards such as FAA SWIM, FIXM/AIXM, and METAR/TAF, and with simulation or queueing concepts.

Responsibilities

Design and build microservices supporting the platform’s Sense → Predict → Orchestrate → Measure operating model.
Integrate real-time data feeds, including ATC, manifests, border processing, detection and security systems, kiosks, and e-Gates; contribute to the AI Detection Algorithm Marketplace.
Build and operate adapters and connectors that normalize diverse source schemas, such as FIXM/AIXM, AODB, and airline feeds, to a canonical event model.
Deliver features such as dynamic staffing allocation, lane management, passenger routing, and predictive maintenance.
Develop calibrated predictive models for queue and wait times, missed connections, baggage, crowding, and disruption propagation; integrate LLM/RAG components for explanation and recommendation while 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 controls.
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.