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Engineering Team Lead, Data Engineer
Canopy
Draper, UT · UT
…lead a high-performing, cross-functional squad of Full Stack Application Engineers, Data Engineers, and QA Engineers to build, scale, and evolve the systems that power our customer-facing…
Added 2 mins ago
SDEII Specialist GenAI Tooling, Specialist Technology Team (STT), AWS WWSO SA Field Initiatives
Amazon Web Services, Inc.
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- 1+ years of software development engineer or related occupational experience
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- $100,000 to $126,000 USD / year
The Brattle Group, a privately held, global economics consulting firm, is looking for a Data and AI Engineer to join our San Francisco, CA office to start in July 2027.
Added 3 mins ago
Senior Network Voice Engineer - TS/SCI Clearance
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AIML - Sr Machine Learning Platform Engineer, Evaluation
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Senior Associate Data Engineering Azure/Databricks Arlington Hybrid
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Data Engineer
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- $60 to $67 USD / hour
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Staff AI/ML Software Engineer - Level 5
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Software Platform Engineer I (Onsite)
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Support and optimize Kubernetes environments for application and platform workloads.
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Senior Feature Engineer
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Closed listing

General Dynamics Information Technology

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

Chantilly, VA, United States

The likely salary range for this position is $161,500 - $218,500.

This opening has closed.

The original listing is kept below for reference.

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About employer

Job details

Pay: The likely salary range for this position is $161,500 - $218,500.
Experience: 8+ years of platform, DevSecOps, SRE, ML engineering, or cloud engineering experience, including 3+ years supporting production AI/ML platforms.
Posting language: English
Posted: Nov 5, 2026

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Original job description

Archived listing. The details below describe a past opening.

Req ID: RQ231678

Type of Requisition: Regular

Clearance Level Must Be Able to Obtain: Top Secret SCI + Polygraph

Public Trust/Other Required: None

Job Family: Data Science and Data Engineering

Skills:

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

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.

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, processing, and use of your biometric data for identity verification and security purposes.

About Our Work:

We are GDIT. A global technology and professional services company that delivers technology solutions and mission services to every major agency across the U.S. government, defense and intelligence community. Our 26,000 experts extract the power of technology to create immediate value and deliver solutions at the edge of innovation. We operate across 50+ countries worldwide, offering leading mission-ready capabilities in AI, cloud, cyber and software development.

Join our Talent Community to stay up to date on our career opportunities and events at https://gdit.com/tc.

Equal Opportunity Employer / Individuals with Disabilities / Protected Veterans

About employer

More about this job

Skills

Data engineering
Supply chain management
ML
Python
Scheduling
ServiceNow
Troubleshoot
Computer science
Machine learning
Computer technology
Linux
Kubernetes
Red Hat OpenShift
CI/CD
IBM Terraform
Ansible
GitLab
Jenkins
Leadership
Coaching
Documentation
PyTorch
Hugging Face
Mlflow
Kubeflow
Microsoft Azure
AWS
DevOps

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