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Senior AI Systems Engineer

SAIC
FULL_TIME Remote ยท US Chantilly, VA, United States, VA, US Posted: 2026-05-11 Until: 2026-07-10
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Job Description
Job ID: 2612038 Location: Chantilly, VA, US Date Posted: 2026-04-30 Category: Engineering and Sciences Subcategory: Systems Engineer Schedule: Full-Time Shift: Day Job Travel: No Minimum Clearance Required: TS.SCI_wPoly Clearance Level Must Be Able to Obtain: None Potential for Remote Work: ORA_ON_SITE Description SAIC is seeking a Senior AI Systems Engineer to provide Systems Engineering and Technical Advisory (SETA) support to a mission critical program in Chantilly, VA. In this role, you will directly support the National Reconnaissance Office's (NRO) Ground Enterprise Directorate (GED)-the organization responsible for architecting, acquiring, and sustaining the nation's most advanced space and ground systems across their full lifecycle. Active Top Secret Clearance with Polygraph is required for this role. As an Senior AI Systems Engineer , you will play a pivotal role in shaping the customer's AI/ML strategy within a key ground segment. You will help drive innovation, guide technical direction, and ensure the delivery of cutting edge, mission aligned AI/ML capabilities. This position is ideal for engineers who thrive at the intersection of advanced analytics, system engineering, and strategic advisory work. Key Responsibilities to include: Collaborate with cross functional teams to define AI/ML project goals, success criteria, and development roadmaps that align with mission priorities. Understand and guide the design of advanced AI/ML models and algorithms, ensuring solutions effectively address complex mission challenges and deliver measurable value. Translate mission and business challenges into AI/ML opportunities, clearly articulating benefits, risks, and tradeoffs to non-technical stakeholders. Stay current on emerging AI/ML technologies, introducing best practices, tools, and methodologies to strengthen the customer's technical posture. Provide mentorship and technical leadership to junior AI/ML practitioners, fostering a culture of innovation and continuous learning. Work closely with customer and vendor data engineers and architects to ensure data pipelines, infrastructure, and compute environments are optimized for model development and deployment. Support vendor teams in rigorous model validation and performance testing, ensuring AI/ML solutions meet mission requirements for accuracy, reliability, and robustness. Qualifications Required Education and Experience: Bachelors and fourteen (14) years or more experience; Masters and twelve (12) years or more experience; PhD or JD and nine (9) years or more experience. Active Top Secret Clearance with Polygraph. 5+ years of industry experience in supporting AI/ML solutions. Experience with cloud computing services (e.g., AWS, Azure, Google Cloud) and their AI/ML offerings. Experience with ML frameworks (e.g., TensorFlow, PyTorch) and programming languages (e.g., Python, R). Experience with data modeling, data pipeline creation, and deployment of ML models in production environments. Experience with DevOps practices, including MLOps, and CI/CD pipelines for AI/ML. Strong analytical and problem-solving skills with the ability to work on complex issues where analysis of situations requires an in-depth evaluation of variable factors. Excellent communication and interpersonal skills, with a proven record of engaging stakeholders and mentoring teams. SAIC is a premier technology integrator providing full life cycle services and solutions in the technical, engineering, intelligence, and enterprise information technology markets. SAIC is Redefining Ingenuity through its deep customer and domain knowledge to enable the delivery of systems engineering and integration offerings for large, complex projects. SAIC's approximately 15,000 employees are driven by integrity and mission focus to serve customers in the U.S. federal government. Headquartered in Reston, Virginia, SAIC has annual revenues of approximately $4.5 billion. For more information, visit saic.com. For information on the benefits SAIC offers, see .