V
Principal AI Engineer
VERISIGN
30 minutes ago
Full-time
On-site
Reston, Virginia, United States
We are building a new engineering team responsible for establishing and operating the company's on-premises Artificial Intelligence and Large Language Model (LLM) platform.
The Principal Engineer
will serve as the senior technical authority for the platform and will help define how AI capabilities are safely, reliably, and effectively implemented throughout the company.
This is a hands-on technical leadership position. The successful candidate will combine strong systems and infrastructure engineering skills with practical knowledge of modern LLMs, inference platforms, developer tooling, and AI-assisted workflows in an enterprise environment.
The Principal Engineer will have substantial influence over architecture, technology selection, engineering standards, operational practices, and the long-term technical direction of the platform. This must be accomplished while continuing the Protect / Grow / Manage framework that guides the company.
Key Responsibilities:
Serve as the principal technical authority for the company's on-premises AI and LLM architecture
Design, implement, operate, and evolve production LLM inference platforms
Evaluate and recommend models, inference engines, developer tools, agent frameworks and supporting technologies
Develop repeatable evaluation methodologies for determining model quality, performance, reliability and suitability for company workloads
Work with Information Security teams to design secure mechanisms for applying LLMs to proprietary source code, internal data, documentation, and analytical workloads
Develop and work with engineering teams to create the most appropriate AI-assisted software engineering capabilities. This includes coding agents, tool use, repository integration, retrieval systems, and related developer workflows
Enhance existing engineering practices and update them to perform, model deployment, upgrades, rollback, observability, capacity planning and incident response
Work closely with security and infrastructure teams to establish appropriate controls for sensitive corporate information
Evaluate emerging AI technologies and distinguish technologies suitable for production use from experimental or immature approaches
Prototype new capabilities and convert successful experiments into reliable production services
Mentor other engineers on the AI platform team and provide technical leadership across organizational boundaries
Work directly with internal users to identify high-value applications for AI, including software development, data analysis, automation, and knowledge retrieval
Required Qualifications:
Bachelor's degree in Computer Science, Information Technology, Telecommunications, or related field or equivalent experience
15+ years computer engineering experience
Strong understanding of distributed systems, networking, storage, containers, and modern infrastructure platforms
Experience with modern software development practices, source control, CI/CD, automation, and infrastructure-as-code
Strong programming or scripting ability in languages such as Python, Go, C/C++ or equivalent
Understanding of LLM inference concepts including context windows, tokenization, quantization, batching, concurrency, memory requirements, and accelerator utilization
Ability to lead major technical initiatives without requiring direct personnel management authority
Excellent written and verbal communication skills
Preferred Qualifications:
Experience in several of the following areas is desirable. Expertise in every area is not expected.
GPU or accelerator-based computing
LLM inference engines such as llama.cpp, vLLM, Ollama, TensorRT-LLM or similar technologies
Kubernetes or other container orchestration platforms
Retrieval-Augmented Generation (RAG), embeddings, vector search, and enterprise knowledge retrieval
Agentic AI systems, tool-calling models, coding agents, or Model Context Protocol (MCP)
AI-assisted software development environments and workflows
Model evaluation, benchmarking, and automated evaluation frameworks
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The Principal Engineer
will serve as the senior technical authority for the platform and will help define how AI capabilities are safely, reliably, and effectively implemented throughout the company.
This is a hands-on technical leadership position. The successful candidate will combine strong systems and infrastructure engineering skills with practical knowledge of modern LLMs, inference platforms, developer tooling, and AI-assisted workflows in an enterprise environment.
The Principal Engineer will have substantial influence over architecture, technology selection, engineering standards, operational practices, and the long-term technical direction of the platform. This must be accomplished while continuing the Protect / Grow / Manage framework that guides the company.
Key Responsibilities:
Serve as the principal technical authority for the company's on-premises AI and LLM architecture
Design, implement, operate, and evolve production LLM inference platforms
Evaluate and recommend models, inference engines, developer tools, agent frameworks and supporting technologies
Develop repeatable evaluation methodologies for determining model quality, performance, reliability and suitability for company workloads
Work with Information Security teams to design secure mechanisms for applying LLMs to proprietary source code, internal data, documentation, and analytical workloads
Develop and work with engineering teams to create the most appropriate AI-assisted software engineering capabilities. This includes coding agents, tool use, repository integration, retrieval systems, and related developer workflows
Enhance existing engineering practices and update them to perform, model deployment, upgrades, rollback, observability, capacity planning and incident response
Work closely with security and infrastructure teams to establish appropriate controls for sensitive corporate information
Evaluate emerging AI technologies and distinguish technologies suitable for production use from experimental or immature approaches
Prototype new capabilities and convert successful experiments into reliable production services
Mentor other engineers on the AI platform team and provide technical leadership across organizational boundaries
Work directly with internal users to identify high-value applications for AI, including software development, data analysis, automation, and knowledge retrieval
Required Qualifications:
Bachelor's degree in Computer Science, Information Technology, Telecommunications, or related field or equivalent experience
15+ years computer engineering experience
Strong understanding of distributed systems, networking, storage, containers, and modern infrastructure platforms
Experience with modern software development practices, source control, CI/CD, automation, and infrastructure-as-code
Strong programming or scripting ability in languages such as Python, Go, C/C++ or equivalent
Understanding of LLM inference concepts including context windows, tokenization, quantization, batching, concurrency, memory requirements, and accelerator utilization
Ability to lead major technical initiatives without requiring direct personnel management authority
Excellent written and verbal communication skills
Preferred Qualifications:
Experience in several of the following areas is desirable. Expertise in every area is not expected.
GPU or accelerator-based computing
LLM inference engines such as llama.cpp, vLLM, Ollama, TensorRT-LLM or similar technologies
Kubernetes or other container orchestration platforms
Retrieval-Augmented Generation (RAG), embeddings, vector search, and enterprise knowledge retrieval
Agentic AI systems, tool-calling models, coding agents, or Model Context Protocol (MCP)
AI-assisted software development environments and workflows
Model evaluation, benchmarking, and automated evaluation frameworks
#J-18808-Ljbffr