Senior Edge AI/ML and Data Engineer

Type of Requisition:

Regular

Clearance Level Must Currently Possess:

None

Clearance Level Must Be Able to Obtain:

Secret

Public Trust/Other Required:

None

Job Family:

Solutions Architect

Job Qualifications:

Skills:

AI Systems, Cloud Applications, Solution Architecture

Certifications:

None

Experience:

10 + years of related experience

US Citizenship Required:

Yes

Job Description:

Influence innovation and problem-focused AI/ML/Data solutions as an AI/ML and Data Solution Architect with the GDIT Defense CTO office. This position works directly with GDIT growth, program, and R&D teams to develop cutting-edge AI/ML/Data solutions for the modern Warfighter.

Position Highlights:

• Role: Lead the architecture and deployment of cutting-edge AI/ML solutions for mission-critical Department of Defense (DoD) operations, with a focus on edge AI, sensor fusion, and generative AI technologies.
• Impact: Drive the adoption of AI/ML solutions to enhance operational effectiveness, situational awareness, and data-driven decision-making in complex DoD environments.
• Innovation: Develop proof-of-concept (PoC) and minimum viable product (MVP) solutions, leveraging advanced AI/ML models in edge computing environments, sensor fusion, and correlation to optimize defense systems.
• Collaboration: Work closely with interdisciplinary teams, including growth, program data scientists, system engineers, cybersecurity experts, and DoD stakeholders, to integrate and align AI solutions with mission objectives.
• Mission-First: Ensure that solutions meet the stringent security, scalability, and reliability requirements necessary for mission success in DoD operations.

Key Responsibilities:

• Design and implement AI/ML solutions with a focus on edge computing to support real-time decision-making in deployed and resource-constrained environments.
• Develop and lead efforts in sensor fusion and correlation, enabling intelligent, data-driven insights from multiple sensor streams.
• Collaborate with teams to rapidly build and test minimum viable products (MVPs) for AI solutions that address DoD-specific operational challenges.
• Architect and support the deployment of generative AI applications, such as AI-driven content generation, scenario simulations, and natural language processing for intelligence operations.
• Utilize data fabric and data mesh architectures to ensure seamless integration, access, and governance of distributed datasets across the DoD's digital infrastructure.
• Ensure compliance with DoD security and operational requirements for AI systems, including cybersecurity, reliability, and performance in mission-critical environments.
• Partner with stakeholders to align AI initiatives with broader strategic objectives of the DoD, focusing on long-term scalability and operational impact.

What you will need to succeed:

Education: BS in Computer Science, Data Science, Data Analytics, or other STEM-related discipline. An MS in one of the described disciplines counts toward four years of experience.

Required Skills and Experience:

• 10+ years of experience in AI/ML solution architecture/Development, with at least 5 years in a leadership role, preferably within the Department of Defense or defense industry.
• Robust background in both cloud-native AI/ML services and DoD-specific cloud environments, with strong emphasis on security, hybrid edge-cloud deployments, multi-cloud AI/ML strategies.
• Deep expertise in edge AI, including designing, deploying, and optimizing models for real-time inference on edge devices in constrained environments.
• Strong background in sensor fusion and correlation techniques, integrating multi-source data to generate actionable intelligence and situational awareness.
• Proven ability to design and lead MVP development processes for AI systems, demonstrating rapid prototyping and iteration to address specific mission needs.
• Experience with Generative AI technologies, such as large language models, AI simulations, and advanced content generation tools relevant to defense use cases.
• Strong understanding of data fabric and data mesh principles, particularly in designing scalable, secure, and agile data architectures within DoD systems.
• Familiarity with DoD cybersecur