C2 SMART AI Engineer

i4DM•Millersville, MD

17h

About The Position

Our employees thrive in a culture that's fast-paced and ego-free, where innovation and collaboration are encouraged at every turn. We are an organization that provides federal agencies and commercial clients instant access to experienced and talented professionals who understand their unique challenges and know the most efficient ways to address them. We are continually investing in resources and talent, so we stay prepared with specialized teams in the place who are experts in creating tailored technologies. Our solutions empower our clients to grow, modernize, and succeed in a rapidly evolving landscape. We value all voices and want to attract talent from all backgrounds. We are on the lookout for individuals who are passionate about technology and thrive in environments where problem-solving is approached with creativity and enthusiasm. If you are someone who enjoys continuously expanding your skill set while tackling real-world business problems, you will feel right at home with us. Veterans and military spouses are especially encouraged to bring your unique and valuable experience to our team. About the role Are you driven to build AI systems that operate where it matters most? As an AI Engineer, you will have a unique opportunity to bridge operational mission needs with advanced artificial intelligence capabilities in support of near real-time situational awareness at the tactical and operational edge. You will play a critical role in designing, developing, and deploying resilient AI models that transform unstructured, free text inputs into structured, actionable information, enabling timely decision making in distributed and DDIL environments. In this role, you’ll develop NLP and generative AI solutions—from SLMs and DSLMs to selectively applied LLMs—engineered to run reliably across edge, on‑prem, and cloud environments, including disconnected and resource‑constrained systems. Working closely with product, DevSecOps, and government stakeholders, you’ll help translate advanced AI into secure, trusted, and operationally impactful solutions.

Requirements

A Bachelor’s degree and 6+ years of technical experience in general, with 3+ years of that experience preferably within the area of Machine Learning and AI.
Strong background in NLP (entity extraction, intent detection, contextual understanding).
Experience designing and deploying deep learning models (classification, sequence, generative).
Hands‑on experience with SLMs, DSLMs, and/or LLMs, including RAG.
Proven track record optimizing models for size/latency (quantization, distillation, pruning; ONNX/TensorRT/OpenVINO helpful).
Experience deploying to edge or small server environments and operating in disconnected/intermittent conditions.
Cross functional collaboration with product, engineering, and DevSecOps roles.
Active Secret clearance or ability to obtain one.

Nice To Haves

Mission/defense experience; familiarity with C2, COP integration, and tactical edge constraints.
Familiarity with Meibel (or strong aptitude to adopt rapidly) for orchestration and lifecycle management.
API architecture/design and performance tuning (REST/gRPC).
VMF and JSON message formats; TAK/ATAK and disconnected operations patterns.
Kafka architecture and development; data tagging/aggregation (e.g., Appian/Kafka).
Experience with Appian platform and data fabric.
Knowledge of DoD cybersecurity (RMF/STIGs), Zero Trust, and data governance.

Responsibilities

Build AI capabilities for digital agents(chatbots) and automated report processing (free text to structured data).
Develop NLP pipelines for entity extraction, intent recognition, normalization, and context understanding for Common Operating Picture (COP) ingestion.
Extend text-centric workflows to multimodal inputs (image/speech) where operationally valuable.
Assist in architecting models for small servers and constrained hardware (e.g., ruggedized x86/ARM, NVIDIA Jetson, Intel NUC).
Define the edge vs. core processing strategy (on device inference, partial offload, opportunistic sync) for disconnected/low bandwidth conditions.
Apply quantization, pruning, distillation, sparse/efficient architectures to meet latency, memory, and power budgets.
Design, fine‑tune, and evaluate SLMs and DSLMs tailored to mission data and reporting formats; selectively leverage LLMs where appropriate.
Implement Retrieval Augmented Generation (RAG) grounded in authoritative doctrine, SOPs, and TTPs to improve accuracy and trust.
Use the Meibel platform for model orchestration, deployment, versioning, and lifecycle management across edge/on-prem/cloud.
Productionize models across edge, on-prem, and cloud; integrate with CI/CD and DevSecOps pipelines.
Implement telemetry, logging, and real-time monitoring with feedback loops for continuous optimization.
Enforce security controls, guardrails, and DoD compliance (e.g., RMF/STIGs, least privilege, data handling).
Build AI platform capabilities for Generative AI and traditional ML; standardize data ingestion, tagging, and pipelines to support the COP.
Integrate AI services with secure APIs, messaging/streaming (e.g., Kafka), and mission systems (VMF/JSON).
Partner with UI/UX to ensure intuitive operator workflows and clear visualization of AI driven insights.
Work with product owners, data scientists, data/ML engineers, and DevSecOps to deliver end-to-end solutions.
Support government stakeholders with adoption, evaluation, and scaling of AI capabilities.