Principal AI Platform and Model Operations Engineer - TS/SCI with Polygraph

Type of Requisition:

Regular

Clearance Level Must Currently Possess:

Top Secret SCI + Polygraph

Clearance Level Must Be Able to Obtain:

Top Secret SCI + Polygraph

Public Trust/Other Required:

None

Job Family:

Data Science and Data Engineering

Job Qualifications:

Skills:

Artificial Intelligence (AI), DevSecOps, Machine Learning (ML) Certifications:

None Experience:

8 + years of related experience US Citizenship Required:

Yes

Job Description:

We are seeking a hands-on AI Platform Operations Engineer to own and mature the end-to-end platform and lifecycle mechanisms that move AI models, prompts, retrieval assets, dependencies, and services from approved development into reliable, classified production environments. This role sits at the intersection of AI engineering, cloud/platform engineering, security, data, and Service Operations, ensuring that advanced AI capabilities can be deployed and operated safely at-scale in highly regulated environments.

You will be responsible for designing and managing a controlled model and software supply chain, implementing local inference services, and orchestrating repeatable release trains for AI workloads. You will establish and enforce standards for observability, capacity management, and safe rollback, operating in environments where every import, deployment, and configuration change is a governed event. This position is ideal for someone who thrives on building robust, secure, and compliant AI platforms that turn experimental solutions into mission-ready, production-grade services.

Key Responsibilities

• •Design and operate AI/ML platform services for local model serving, orchestration, model and artifact registries, experiment/evaluation tracking, feature or retrieval assets, and deployment automation.
• •Build controlled import and release workflows for model weights, containers, Python packages, libraries, prompts, datasets, and vulnerability updates in disconnected environments.
• •Implement provenance, checksums/signing, SBOMs, malware/vulnerability scans, license review, allowlists, approvals, staged validation, and rollback for AI artifacts.
• •Deploy and tune inference services using approved serving stacks; manage batching, concurrency, memory, quantization, autoscaling where available, queueing, resilience, and graceful degradation.
• •Establish versioning and release relationships among model, tokenizer, prompt, retrieval index, embedding model, configuration, evaluation set, application, and infrastructure.
• •Develop GPU/CPU/storage/network capacity models and advise on hardware options, consolidation, scheduling, and cost/performance trade-offs.
• •Implement health, latency, throughput, saturation, failure, quality, drift, and usage telemetry integrated with enterprise observability and ServiceNow.
• •Define backup/recovery, continuity, patching, vulnerability treatment, certificate/secret rotation, and incident procedures for AI platform services.
• •Partner with AI Assurance and Security to enforce use-case gates, evaluation thresholds, audit, data restrictions, and release evidence.
• •Lead technical reviews, troubleshoot production AI platform incidents, mentor engineers, and document reusable platform patterns.

Required Qualifications

• •Education: Bachelor’s degree in computer science, Software Engineering, Machine Learning, Information Technology, or related field, or approved equivalent experience.
• •Location: Onsite
• •Clearance: Active TS/SCI with Polygraph
• •8+ years of platform, DevSecOps, SRE, ML engineering, or cloud engineering experience, including 3+ years supporting production AI/ML platforms.
• •Hands-on experience deploying and operating local model-serving platforms such as vLLM, TGI, Triton, TensorRT-LLM, llama.cpp, Ollama, ONNX Runtime, or comparable technologies.
• •Strong Linux, container, Kubernetes/OpenShift, networking, storage, GPU, identity, secrets, and infrastructure automation skills.
• •Experience with model/artifact registries, experiment tracking, release management, CI/CD, internal package/container repositories, and disconnected dependency management.
• •Ability to size inference capacity using model precision, VRAM, context length, concurrency, throughput, latency, and availability requirements.
• •Strong Python and automation proficiency plus experience with Terraform, Ansible, Helm, GitLab CI/Jenkins, or comparable tooling.
• •Working knowledge of RMF/STIG, software supply-chain security, SBOMs, vulnerability management, logging/audit, and classified data handling.
• •Demonstrated technical leadership, incident judgment, cross-team coordination, mentoring, and clear documentation.

Preferred Qualifications

• •Experience with PyTorch, Hugging Face, MLflow, Kubeflow, Ray, NVIDIA GPU tooling, CUDA, or enterprise AI platform products.
• •Experience operating A100, H100, L40S, or comparable accelerators and performing quantization/optimization.
• •Experience with Azure Government, AWS GovCloud, C2S-equivalent, or on-premises platform delivery.
• •Role-relevant CKA/CKS, current Red Hat platform engineering credentials, or Microsoft Certified: DevOps Engineer Expert. Relevant Terraform, NVIDIA or ML-platform credentials
• •Experience integrating model-quality/evaluation signals with deployment gates and production monitoring.

GDIT IS YOUR PLACE

At GDIT, the mission is our purpose, and our people are at the center of everything we do.

• •Growth: AI-powered career tool that identifies career steps and learning opportunities
• •Support: An internal mobility team focused on helping you achieve your career goals
• •Rewards: Comprehensive benefits and wellness packages, 401K with company match, and competitive pay and paid time off
• •Community: Award-winning culture of innovation and a military-friendly workplace

OWN YOUR OPPORTUNITY Explore a career in data science and engineering at GDIT and you’ll find endless opportunities to grow alongside colleagues who share your determination for solving complex data challenges.

#GDITcareers #OpportunityOwned

#WeAreGDIT #transitioningmilitary

#clearedjobs #veterans #Autobots

#IntelligenceEngineered

The likely salary range for this position is $161,500 - $218,500. This is not, however, a guarantee of compensation or salary. Rather, salary will be set based on experience, geographic location and possibly contractual requirements and could fall outside of this range.

Scheduled Weekly Hours:

40

Travel Required:

None

T elecommuting Options:

Onsite

Work Location:

USA VA Chantilly

Additional Work Locations:

Total Rewards at GDIT:

Our benefits package for all US-based employees includes a variety of medical plan options, some with Health Savings Accounts, dental plan options, a vision plan, and a 401(k) plan offering the ability to contribute both pre and post-tax dollars up to the IRS annual limits and receive a company match. To encourage work/life balance, GDIT offers employees full flex work weeks where possible and a variety of paid time off plans, including vacation, sick and personal time, holidays, paid parental, military, bereavement and jury duty leave. To ensure our employees are able to protect their income, other offerings such as short and long-term disability benefits, life, accidental death and dismemberment, personal accident, critical illness and business travel and accident insurance are provided or available. We regularly review our Total Rewards package to ensure our offerings are competitive and reflect what our employees have told us they value most.

Our Identity Verification Process:

As part of the hiring process, we will ask you to complete an identity verification process that leverages advanced biometrics and artificial intelligence to ensure authenticity and protect against identity fraud. You are expected to be on camera during virtual interviews. We reserve the right to take your picture to verify your identity and prevent fraud. By proceeding, you authorize the collection, proces