AI/ML & Systems Engineer
Leif P. Heaney
Build intelligent systems that transform complex data into actionable insights & confident decisions — across applied AI, systems engineering, edge deployment, and federal programs.
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Full Résumé
Experience, education & skills.
AI/ML and systems engineer with experience designing data-intensive applications, model-based architectures, intelligent automation, and edge-deployable systems for complex operational environments. I connect implementation, verification, and technical communication across industry and higher education.
Core Competencies
Soft Skills
Professional Experience
Reveal Technology
Systems Engineer
2026 – Present · Bozeman, MT
Engineer backend infrastructure and edge deployment strategies that unify global location telemetry, behavioral analytics, and high-resolution geospatial data for real-time, offline-capable situational awareness.
- Design and optimize end-to-end systems for deploying edge AI and computer vision models in disconnected, intermittent, and limited (DIL) environments.
- Engineer robust deployment pipelines using Docker and Kubernetes to manage containerized AI workloads across tactical edge devices.
- Interface with cross-functional teams to translate complex tactical requirements into technical specifications, bridging software development and hardware constraints for defense-centric AI solutions.
- Architect and maintain geospatial data pipelines supporting high-fidelity, real-time mapping and 3D reconstruction for tactical intelligence.
- Design and govern scalable data lakes for secure storage and retrieval of massive computer vision datasets with automated metadata tagging.
The MITRE Corporation
Systems Engineer, Intermediate
2021 – 2025 · McLean, VA
Spearheaded systems engineering across program lifecycle — from requirements definition to deployment — for federal programs across DoD, DHS, and HHS. Maintained traceability via MBSE/SysML, digital twins, and digital threads.
- Automated data processing with end-to-end ETL pipelines and custom models for data-driven decision making.
- Hardened COMSEC systems through implementation of DoD Zero Trust Architecture (ZTA), ensuring regulatory compliance.
- Developed comprehensive MBSE reference architecture and high-fidelity digital twins, enhancing system resilience, traceability, and transparency.
- Designed and delivered 12+ DoDAF/UAF views and SysML diagrams for federal programs, documenting complex system architectures, interfaces, and behavior.
- Developed interactive GIS dashboards integrating LPR technology and open-source GIS data in QGIS, enabling pattern-of-life analysis and prioritization of 3 high-risk locations.
Capitol Technology University
Adjunct Faculty — Computer Science Department
2022 – Present · Laurel, MD
Led instruction and subject-matter expertise across Computer Science and Information Assurance for 100+ students over 4 years. Drove 2 end-to-end curriculum overhauls for CS-120: Intro to Programming with Python (6 sections taught).
- Served as SME and instructor for IAE-574: Assured Software Analytics, integrating contemporary methodologies across labs, eLearning, and assessments over 3+ years.
- Bridged theory and application by integrating industry best practices and real-world cases into curriculum, enhancing students' practical relevance and employability.
Education
Master of Science (MS) — Computer Science
Capitol Technology University · Laurel, MD · 2022 · GPA 3.86
Bachelor of Science (BS) — Computer Science
Capitol Technology University · Laurel, MD · 2020 · GPA 3.5
Clearance
- SECRET — Department of Defense (DoD)
- S&T EOD IT 5C (Medium) — Department of Homeland Security (DHS)
- MBI (Moderate) — Internal Revenue Service (IRS)
Industry Experience
Tech Stack
Languages & Runtime
AI/ML & Data
Geospatial & Viz
Cloud & DevOps
MBSE & Systems
Web & Application Engineering