AI Forward Deployed Engineer (FDE)

NetCentrics Corporation•Herndon, VA

About The Position

At NetCentrics, we are not looking for someone who simply talks about artificial intelligence, we are looking for someone who can architect it, build it, and deploy it securely in real federal mission environments. As our AI Forward Deployed Engineer (FDE), you will lead the design and delivery of AI solutions that directly support national security and federal mission priorities. This role sits at the intersection of strategy, architecture, and hands-on engineering, requiring both technical depth and the ability to translate emerging AI capabilities into real operational outcomes. Unlike large integrators where AI architects often become small parts of large bureaucratic teams, this position offers true ownership, visibility, and the opportunity to shape how AI is implemented across both our organization and client environments. If you are someone who wants to move beyond theory and PowerPoint decks and instead build AI systems that are actually deployed and used, we want to talk.

Requirements

Must be a U.S. citizen
7+ years of experience in technical consulting, solution architecture, field engineering, or similar roles with a focus on AI/ML.
Proven success leading AI/ML initiatives from concept through production.
Demonstrated ability to manage complex, high-visibility technical programs.
Deep hands-on experience with: LLM-based systems and Generative AI pipelines, Prompt engineering, RAG, and orchestration frameworks (e.g., LangChain, Semantic Kernel), Custom software development
Strong cloud architecture experience (AWS, Azure, or GCP).
Expertise with: Containers (Docker, Kubernetes), Infrastructure-as-Code (Terraform or similar), Enterprise integration patterns
Exceptional communication and presentation skills.
Ability to translate complex technical concepts into mission and business impact.
Strong analytical and architectural problem-solving skills.
Customer-focused mindset with emphasis on measurable outcomes.

Nice To Haves

Proficiency in Python and SQL.
Experience working within federal data governance and security environments.
Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or related technical discipline.
Experience supporting DoD, DHS, or Federal Civilian agencies.

Responsibilities

Lead AI Strategy for Real Missions: Partner with federal stakeholders to identify high-impact AI opportunities and translate mission needs into actionable AI solutions. Shape AI strategy, technical roadmaps, and implementation plans aligned with program and national security priorities. Serve as the senior technical authority guiding AI architecture decisions across programs and initiatives.
Architect & Build AI Systems: Design and implement end-to-end AI/ML solutions, including: Large Language Models (LLMs), Retrieval-Augmented Generation (RAG) architectures, Vector databases and modern data architectures, AI workflow orchestration frameworks. Architect secure, scalable AI-native platforms capable of enterprise deployment in federal environments. Lead hands-on prototyping and proof-of-concept development to validate technical feasibility and mission impact.
Drive Delivery from Concept to Deployment: Work closely with engineering teams to rapidly prototype, test, and iterate solutions. Guide solutions through the full lifecycle — concept ? prototype ? production deployment. Incorporate operational feedback and mission insights to continuously improve platforms and architectures.
Engage with Clients & Leadership: Act as the primary technical liaison between government customers, internal teams, and external partners. Present architectural approaches and AI strategies to executive leadership and senior stakeholders. Translate complex AI concepts into clear, actionable insights for both technical and non-technical audiences.
Ensure Security, Compliance & Responsible AI: Architect solutions that meet federal security and compliance frameworks, including RMF and FedRAMP. Ensure solutions follow ethical AI practices and strong data governance standards. Design secure AI systems deployed within AWS, Azure, or GCP cloud environments.