---
title: 'Edge AI/Model Optimization Engineer at NextGen Federal Systems'
canonical: 'https://feeny.ai/job/edge-ai-model-optimization-engineer-nextgen-federal-systems-aberdeen-584d7jr45jev'
type: 'job'
last_seen: '2026-09-08'
---

# Edge AI/Model Optimization Engineer at NextGen Federal Systems

- **Company:** NextGen Federal Systems
- **Location:** Aberdeen, MD
- **Employment:** full-time
- **Work type:** hybrid
- **Posted:** 2026-05-21
- **Last confirmed live:** 2026-09-08
- **Apply:** https://jobs.lever.co/nextgenfed/414bed25-dc3b-472a-abc5-8c6d1aaf7820

## Job description

NextGen is seeking a highly motivated and technically skilled Edge AI/Model Optimization Engineer to support the deployment, optimization, and sustainment of AI and agentic AI capabilities within edge and tactical computing environments. This role focuses on evaluating, tuning, benchmarking, and operationalizing Large Language Models (LLMs), embedding models, and AI inference services for constrained hardware platforms, including the X9 Spider Mission Computer architecture and other edge compute systems supporting operational missions using ReadiChat. ReadiChat is a mission-focused, agentic AI platform designed to help organizations build, deploy, govern, and scale specialized AI agents for operational workflows. It combines AI agents, workflow orchestration, grounded knowledge, testing frameworks, and enterprise controls into a single collaborative workspace. The ideal candidate will possess expertise in AI model optimization, GPU-enabled edge computing, runtime performance tuning, and operational AI deployment. This role requires close collaboration with AI engineers, systems integrators, mission stakeholders, and operational users to ensure AI-enabled capabilities remain performant, reliable, and mission-effective within disconnected, degraded, intermittent, and low-bandwidth environments.

## Responsibilities

- Evaluate candidate Large Language Models (LLMs), embedding models, and AI inference solutions for quality, latency, memory utilization, reliability, and operational performance on embedded GPU-enabled edge compute platforms, including the X9 Spider Mission Computer architecture.
- Tune and optimize AI model runtime configurations for edge deployment, including quantization strategies, batching configurations, context window sizing, cache behavior, inference scheduling, and GPU memory utilization specific to operational edge hardware environments.
- Collaborate with customer stakeholders to assess mission requirements and evaluate alternative edge compute platforms when operational demands exceed X9 Spider capabilities or when cost, performance, power, size, weight, or thermal tradeoffs require additional analysis.
- Benchmark agentic AI workflows, inference pipelines, and model-serving architectures against target hardware constraints and operational performance thresholds.
- Recommend model-selection, runtime, and configuration tradeoffs balancing mission effectiveness, latency, throughput, resource utilization, reliability, and operational sustainability.
- Build and maintain repeatable performance and stress-testing frameworks for evaluating latency, throughput, tool-call overhead, failover behavior, degraded-resource conditions, and disconnected operational scenarios on edge compute platforms.
- Package, deploy, validate, and sustain local model-serving components and inference services to support reliable operation within tactical and edge environments.
- Collaborate with agent engineers, AI developers, and integration teams to validate that agent behavior, workflow reliability, and operational outcomes remain acceptable following model compression, quantization, runtime optimization, or hardware configuration changes.
- Support deployment, troubleshooting, optimization, and sustainment activities for AI-enabled applications operating in edge, airborne, tactical, or disconnected operational environments.
- Train customer technical personnel on supported model profiles, operational constraints, runtime tuning considerations, deployment limitations, troubleshooting procedures, and platform sustainment best practices.
- Maintain technical documentation, benchmarking results, model validation reports, deployment procedures, optimization baselines, configuration guides, and operational support materials.
- Support DevSecOps and CI/CD activities associated with AI model packaging, deployment automation, runtime validation, and operational release processes.

Required Qualifications

- Bachelor’s degree in Computer Science, Electrical Engineering, Computer Engineering, Data Science, Artificial Intelligence, or related technical discipline.
- 5+ years of experience supporting AI/ML deployment, model optimization, edge computing, GPU acceleration, or AI inference operations.
- Experience deploying and optimizing LLMs, embedding models, or AI inference pipelines within resource-constrained or edge-compute environments.
- Experience with GPU-enabled systems and inference optimization technologies such as CUDA, TensorRT, ONNX Runtime, vLLM, Ollama, or equivalent platforms.
- Experience tuning AI runtime configurations including quantization, batching, caching, and memory optimization techniques.
- Experience benchmarking AI models and operational workflows against hardware performance constraints.
- Experience with Linux-based systems, containerized deployments, and orchestration technologies such as Docker and Kubernetes.
- Familiarity with Python and AI/ML deployment frameworks commonly used for edge inference and operational AI systems.
- Strong analytical, troubleshooting, and performance optimization skills.
- Ability to communicate technical findings and operational tradeoffs effectively to technical and non-technical stakeholders.
- Active Security Clearance is required

Desired Qualifications

- Experience supporting tactical, airborne, or mission-command edge computing environments.
- Familiarity with X9 Spider Mission Computer architectures or similar embedded GPU-enabled mission systems.
- Experience supporting AI-enabled workflows within NGC2, AIDP, EMSCO, Lattice, or related operational ecosystems.
- Experience with model quantization techniques such as INT8, FP16, GGUF, GPTQ, AWQ, or similar optimization approaches.
- Familiarity with disconnected, degraded, intermittent, and low-bandwidth (DDIL) operational environments.
- Experience with hardware evaluation and performance trade studies for operational edge compute systems.

About NextGen: NextGen Federal Systems is an innovative technology and professional services provider specializing in advanced software solutions and comprehensive mission and business support services. We work in close collaboration with our customers to truly understand their business and mission goals. Our approach is to design, build, implement, and manage solutions that measurably improve our client’s organizational performance. We have established and foster a corporate culture where we: Treat employees with fairness and respect regardless of their position, sexual identity, race, or tenure. Communicate the importance of our mission and our employees’ contributions to it, ensuring they understand how their job role contributes to the greater good. Openly promote and communicate our ideas for change and adaptability. Strive to achieve results as an organization. Hold employees accountable to their commitments and provide incentives that encourage positive and productive behaviors. Value the talents and contributions of our employees as the key factor for our success. Create an environment where people can engage at all levels. Encourage people to take risks and allow them to make mistakes.

Equal Opportunity Employer/Protected Veterans/Individuals with Disabilities.

RefID: A01

## About NextGen Federal Systems

## Company Overview
- **One-liner**: NextGen Federal Systems is a mission-focused IT solutions and services provider delivering modern software engineering, AI/ML, digital engineering, and complex mission support to defense, intelligence, and federal customers.
- **Entity Type**: Private (no funding rounds disclosed; organic/steady growth)
- **Headquarters**: Morgantown, West Virginia, United States (with offices in Aberdeen, MD; Dayton, OH; O’Fallon, IL; and additional locations in Beavercreek, OH, Belcamp, MD, Parker, CO, Springfield, VA, Fort Meade, MD, and Washington, DC areas)  
- **Founded**: 2011  
- **Founders**: Jay Reddy (Founder & CEO); Chetan Desai serves as COO ([nextgenfed.com/leadership](https://www.nextgenfed.com/leadership/))

## Core Business
- **Primary industries**: Defense, Intelligence, Federal IT services, Software Engineering, AI/ML, Digital Engineering, Modeling & Simulation
- **Target customers**: B2G — U.S. Department of Defense, intelligence agencies, federal civilian agencies, and commercial companies
- **Mission**: "NextGen is committed to enabling mission success and driving innovation that shapes the future of national security and beyond" ([LinkedIn](https://linkedin.com/company/nextgenfed))

## Products & Services
- **Federal Mission AI Platform**: Secure, governable agent-publishing environment built for operational domains, including "Weather Wingman Agents" and other mission-specific AI agents.
- **ReadiChat**: Secure AI platform for mission-specific agents — an "AI-assisted agent factory" enabling custom workflows, mission-ready agents, and domain-specific capabilities such as electronic warfare agents.
- **Weather Analyst®**: Weather forecasting and analysis tool that delivers user-tailored advisories, platform/sensor impact rules, and decision support for mitigating or exploiting weather conditions.
- **StratusML®**: A machine learning platform with a hardened, modular codebase, reproducible results, secure ML prototyping, low-code/no-code workflows, and Govcloud accreditation.
- **Digital Arsenal**: Secure DevSecOps (DSO) platform with ATO for AWS GovCloud, code security scans, automated testing, Platform as Code (PaC) compliance (cATO-compliant), and tenant onboarding.
- **SADIE™**: Constructive and high-fidelity simulation platform that automates simulation execution and supports Digital Mission Engineering (DME) threat analysis.
- **Professional Services**: Modern software engineering, AI/ML, digital engineering, complex mission support, CI/CD automation, cloud-native development, continuous testing, human-centered design, and secure system development ([nextgenfed.com](https://www.nextgenfed.com/))

## Market Standing
- **Valuation/Market Cap**: Not disclosed (private company)
- **Key Metric**: Estimated annual revenue of **$36.6M** and **183 employees** (down 1.9% YoY, -5 people) based on LinkedIn company data ([LinkedIn](https://linkedin.com/company/nextgenfed))
- **Notable Investors/Partners**: No external investors disclosed. Key customers span DoD, Intelligence, and Federal markets. Certifications include ISO 9001 and CMMI-DEV/CMMI-SVC Level 3.
- **Growth Signals**: Recognized by the INC 5000 as one of the fastest-growing companies in the U.S. in **nine of the last ten years**; steady expansion of office locations and job openings across Maryland, Ohio, Illinois, West Virginia, Virginia, Colorado, and Washington, DC ([nextgenfed.com](https://www.nextgenfed.com/))

## Competitive Advantages
- **Dual model of services and product development**: Combines government services contracts with proprietary, saleable platforms — rare among smaller federal contractors.
- **Secure AI/ML platforms built for the mission environment**: Govcloud-accredited products like StratusML and Digital Arsenal address strict federal security and compliance requirements.
- **Deep domain specialization**: Focus on defense, intelligence, electronic warfare, weather, and digital mission engineering creates high barriers to entry.
- **Mature engineering processes**: CMMI-DEV Level 3, CMMI-SVC Level 3, and ISO 9001 certification signal disciplined delivery.
- **Employee-centric culture**: High ratings (4.3/5 on LinkedIn from 65 reviews) and testimonials emphasize collaboration, trust, transparency, and a people-first approach that supports retention and recruiting ([LinkedIn](https://linkedin.com/company/nextgenfed))

## Strategic Focus
- **Scaling AI/agentic AI for federal missions**: Hiring "Application/Agentic AI Engineer" and "Edge AI/Model Optimization Engineer" roles indicates a push toward on-device and agent-driven AI solutions.
- **Expanding DevSecOps and cloud-native infrastructure**: Digital Arsenal and DevSecOps roles point to continued investment in secure software delivery pipelines.
- **Enhancing digital engineering and simulation**: SADIE and modeling & simulation hires align with DoD’s shift toward digital mission engineering and simulation-based testing.
- **Supporting multi-location growth**: Open positions span multiple states, suggesting geographic expansion of delivery and client-facing teams ([jobs.lever.co/nextgenfed](https://jobs.lever.co/nextgenfed))

## Why Work Here
- **Culture**: Employees describe a "collaborative, people-first culture" with approachable, transparent leadership and a "close-knit, respectful environment" even as the company grows.
- **Work style**: Teams are distributed and flexible. Employees report the ability to "manage their work while continuing to learn and grow" and a "shared commitment to delivering great outcomes for customers."
- **Engineering experience**: A "technology-focused environment where your ideas are welcomed, your development is encouraged, and everyone is working toward the same goals." Knowledge-sharing sessions, technical learning, and cross-team collaboration are common.
- **Perks and engagement**: Team lunches, HR check-ins, technical knowledge-sharing sessions, and opportunities to take initiative.
- **Reviews**: LinkedIn employer rating of **4.3/5** with sub-scores: Work-Life 4.3, Compensation 3.9, Culture 4.3, Career 4.0 ([nextgenfed.com/careers](https://www.nextgenfed.com/careers/)) ([LinkedIn](https://linkedin.com/company/nextgenfed))

## Sources
1. [NextGen Federal Systems — Main website](https://www.nextgenfed.com/)
2. [NextGen Federal Systems — Careers](https://www.nextgenfed.com/careers/)
3. [NextGen Federal Systems — Lever job board](https://jobs.lever.co/nextgenfed)
4. [NextGen Federal Systems — Leadership](https://www.nextgenfed.com/leadership/)
5. [NextGen Federal Systems — LinkedIn company page](https://linkedin.com/company/nextgenfed)

## Other roles at NextGen Federal Systems

- [VDI Platform Engineer](https://feeny.ai/job/vdi-platform-engineer-nextgen-federal-systems-dayton-bpw0eqd0yjvp) — Dayton, OH
- [Systems Administrator](https://feeny.ai/job/systems-administrator-nextgen-federal-systems-beavercreek-hx2zmrx4k2ys) — Beavercreek, OH
- [VDI Engineer](https://feeny.ai/job/vdi-engineer-nextgen-federal-systems-beavercreek-64a1b3hd2kws) — Beavercreek, OH
- [Chief MS&A Engineer](https://feeny.ai/job/chief-ms-a-engineer-nextgen-federal-systems-dayton-mx7pb31wkgps) — Dayton, OH
- [Cloud Solutions Engineer (Data & Platform)](https://feeny.ai/job/cloud-solutions-engineer-data-platform-nextgen-federal-systems-falls-church-5pnxn3mbkzfa) — Falls Church, VA
- [Senior Systems Engineer](https://feeny.ai/job/senior-systems-engineer-nextgen-federal-systems-dayton-tjfearqr5ks2) — Dayton, OH
- [Tech Lead Principal Systems Engineer](https://feeny.ai/job/tech-lead-principal-systems-engineer-nextgen-federal-systems-dayton-8454dq6a48g1) — Dayton, OH
- [Senior Engineering Manager / Analyst](https://feeny.ai/job/senior-engineering-manager-analyst-nextgen-federal-systems-washington-ssr5nr7e0k37) — Washington, DC
- [Senior Procurement Manager / Analyst](https://feeny.ai/job/senior-procurement-manager-analyst-nextgen-federal-systems-washington-21kshnjwmycb) — Washington, DC
- [Information Security Analyst](https://feeny.ai/job/information-security-analyst-nextgen-federal-systems-washington-wxkfysbc4437) — Washington, DC