SAIC is seeking a highly experienced and motivated Senior Software Engineer to contribute to the integration of AI capabilities into expeditionary systems, including sensor kits, UxS, C2, and TAK. The successful candidate will play a key role in enhancing the capabilities of expeditionary systems through innovative and cutting-edge technologies. Daily tasks can vary from hands on keyboard to technical discussions, including but not limited to, maintaining real-time Zenoh data mesh in Rust, creating frontend React applications in JavaScript, working with AI engineers to integrate machine learning models, converting data between standard tactical message formats, or providing subject matter expertise in discussions with senior management.
Locations willing to consider future candidate:
This roles is 100% ON-SITE, must be nearby one of the following locations but if San Diego, CA is not your primary location you will be required to travel to San Diego, CA for at least 5 weeks a year for team meetings and administrative tasks.
- San Diego, CA
- Arlington, VA
- Colorado Springs, CO
- Charleston, SC
- Denver, CO
JOB DUTIES:
- Collaborate with cross-functional teams to understand and address the Navy's operational challenges integrating artificial intelligence into expeditionary systems.
- Design, develop, and implement software for tactical applications
- Test software at field experiments to ensure performant and high-quality data flow between tactical systems, including sensors, UxS, and C2
- Collaborate with machine learning engineers and domain experts to analyze data and integrate machine learning solutions into existing systems.
- Collaborate with data engineers to monitor data pipelines and analytics to ensure accuracy, reliability, and robustness.
- Stay updated with the latest advancements in data architecture to propose and implement innovative solutions.
- Work closely with systems engineers to connect data pipelines with operational systems
- Provide technical expertise and contribute to the development of long-term technology strategies within the Department of the Navy.
REQUIREMENTS:
- Bachelors in Computer Science, Data Science, Geography, Math, Machine Learning, or Statistics and nine (9) years or more experience. Years of experience in lieu of degree to be taken into consideration.
- Must be a U.S. Citizen.
- Must have an Active Secret Clearance to start.
- Must be able to obtain a TS/SCI clearance after start.
- At least 9 years experience working as a business analyst, data analyst, data scientist, data engineer, database administrator, geospatial analyst, geospatial engineer, IT specialist, machine learning engineer, software engineer, or system administrator.
- Familiarity with containerization technologies (e.g., Docker, Kubernetes).
- Expert programming skills in Python.
- Intermediate programming skills in Rust or Go.
- Experience designing or normalizing tactical data to common standards.
- Experience with multiple data formats, e.g., CSV, JSON, XML, Parquet, ORC.
- Familiarity with event streaming libraries and platforms, e.g., Apache Kafka, AWS Kinesis, RabbitMQ, ZeroMQ, or Zenoh.
- Experience with troubleshooting tactical systems.
- Experience deploying, monitoring, and improving tactical data pipelines.
- Strong problem-solving and analytical skills.
- Passion for staying updated with the latest advancements in tactical data architecture.
- Excellent communication skills and the ability to work effectively in a collaborative team environment.
DESIRED SKILLS:
- Experience integrating systems with Tactical Assault Kit (TAK) ecosystem.
- Familiarity with data pipeline frameworks and libraries, e.g., AirByte, Apache Airflow, dbt, Apache Iceberg, Snowflake.
- Experience with adding and retrieving data from Geographic Information Systems (GIS), e.g., ArcGIS, PostGIS.
- Expertise in Elasticsearch, Redis, S3, PostgreSQL, or other data stores.
- Understanding of cybersecurity principles in the context of tactical applications.
- Previous experience working with government agencies or military organizations.
- Master of Science in Computer Science, Data Science, Geography, Math, Machine Learning, or Statistics.