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Principal AI Enablement Engineer

Verisign Inc/Ca

Reston, VA · Posted October 28, 2026

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Skills this job asks for

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  • Python
  • Audit
  • CI/CD
  • Kubernetes
  • Linux

About the job

Verisign helps enable the security, stability, and resiliency of the internet. We are a trusted provider of internet infrastructure services for the networked world and deliver unmatched performance in domain name system (DNS) services.

We are a mission focused, values driven company where each individual can contribute to building a stronger, more secure internet. We offer a dynamic and flexible work environment with competitive benefits and the ability to grow your career.

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

Extensive experience designing, operating or troubleshooting complex production systems

Strong Linux systems 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

Practical experience deploying LLMs

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

Open-weight LLM deployment and model lifecycle management

Enterprise authentication, authorization, secrets management, and audit systems

Working in environments with strict security, privacy, reliability or regulatory requirements

Security and Responsible AI Expectations

Security and governance are central to this role. The AI Enablement Engineer will be expected to help technical teams adopt AI capabilities in a manner that protects company data, aligns with approved use policies, and supports responsible AI practices.

This includes understanding how AI tools interact with sensitive information, how access to AI capabilities should be controlled, and how technical users can safely incorporate AI into engineering workflows. The role requires a strong security mindset and the ability to work closely with governance, security, and platform stakeholders.

This position is based in our Reston, VA office and offers a hybrid work schedule.

The pay range is $180,700 - $244,500.

The anticipated annual base salary range for this position is noted above, however, base pay offered may vary depending on job-related knowledge, skills, experience. Verisign offers a discretionary bonus which is based on individual and company performance, and certain roles may be eligible for discretionary stock awards.

Verisign is an equal opportunity employer. That means we recruit, hire, compensate, train, promote, transfer, and administer all terms and conditions of employment without regard to their race, color, religion, national origin, sex, sexual orientation, gender identity, age, protected veteran status, disability, or other protected categories under applicable law.

Additional Information: Our Careers Page Our Benefits Summary Verisign in the Community Our EEO Statement Our Privacy Notice for Job Applicants/Candidates Reasonable Accommodations

Staffing agency policy: No fees will be paid for unsolicited resumes submitted to Verisign or our employees by third parties.