2

Remote Ai Engineer Jobs in Virginia (NOW HIRING)

This is a remote position. The ideal candidate is a hands-on AI/ML engineer who can develop, evaluate, tune, and operationalize secure and maintainable AI capabilities for FEMA mission programs. This ...

We're looking for an experienced AI Software Engineer with 6-8 years of experience to join our AI applications team. This is a fully remote position for candidates in the continental U.S., with work ...

TestPros is seeking a Senior Artificial Intelligence (AI) System Test Engineer with an analytical ... Remote, with occasional travel to customer sites or TestPros labs in Sterling, VA This role ...

ICF is seeking an AI / Automation Engineer to design, build, and continuously improve the AI ... Job Location: This is a remote-friendly position with occasional onsite requirements in the ...

AI Systems Engineer

Chantilly, VA · On-site +1

$200K - $240K/yr

None Potential for Remote Work: ORA_ON_SITE Description  SAIC is seeking a highly skilled AI/ML Systems Engineer to provide Systems Engineering and Technical Advisory (SETA) support to a mission ...

AI Data Engineer

Fort Belvoir, VA · On-site +1

$160K - $200K/yr

TS/SCI with Poly Potential for Remote Work: ORA_ON_SITE Description SAIC is seeking an AI Data Engineer to join our team at Fort Belvoir, Virginia. The AI Data Engineer will design, develop, and ...

AI/ML Engineer

Chantilly, VA · On-site +1

$99K - $225K/yr

Remote Work: No Job Number: R0245425 Location: Chantilly,VA,US Share job via: Share AI/ML Engineer The Opportunity: Data scientists and intelligence analysts rely on multi-step workflows that are ...

Showing results 21-40

Remote Ai Engineer information

What is a remote AI engineer?

A Remote AI Engineer is a professional who designs, develops, and deploys artificial intelligence models and systems while working from a remote location. They use machine learning, deep learning, and data science techniques to build AI-powered applications, improve automation, and solve complex problems. Responsibilities often include data preprocessing, model training, fine-tuning, and integrating AI solutions into products or services. These engineers collaborate with cross-functional teams online, using cloud-based tools and platforms for development and deployment. Remote AI Engineers typically need strong programming skills in languages like Python, experience with frameworks like TensorFlow or PyTorch, and familiarity with cloud computing and MLOps.

What is it like collaborating with team members as a remote AI engineer?

As a Remote AI Engineer, collaboration typically occurs through virtual meetings, code reviews, shared documentation, and messaging platforms like Slack or Teams. You will work closely with data scientists, product managers, and software engineers to define requirements, design solutions, and integrate AI models into products or services. Strong communication and proactive reporting are highly valued to ensure project alignment and seamless progress. Effective collaboration in a remote setting not only enhances project outcomes but also fosters professional growth and a sense of team cohesion.

What are the most commonly searched types of Ai Engineer jobs in Virginia?

The most popular types of Ai Engineer jobs in Virginia are:

What are popular job titles related to Remote Ai Engineer jobs in Virginia?

For Remote Ai Engineer jobs in Virginia, the most frequently searched job titles are:

What job categories do people searching Remote Ai Engineer jobs in Virginia look for?

The top searched job categories for Remote Ai Engineer jobs in Virginia are:

What cities in Virginia are hiring for Remote Ai Engineer jobs?

Cities in Virginia with the most Remote Ai Engineer job openings:

Infographic showing various Remote Ai Engineer job openings in Virginia as of August 2026, with employment types broken down into 2% Internship, 79% Full Time, and 19% Contract. Highlights an 100% Remote job distribution.

AI Workflow Engineer

Ultimate Knowledge

Chesapeake, VA • Remote

Full-time

Posted 14 days ago


Job description

Build the Agentic Software Factory

AI is rewriting how software gets built and most organizations are still bolting chatbots onto yesterday's process. We're doing something different. UKi is looking for an AI Workflow Engineers to architect our agentic SDLC from the ground up: formalized pipelines where AI agents plan, build, test, review, and ship alongside a core team of skilled senior US-based engineers, with the governance, grounding, and measurement to prove it works.

This isn't a research role and it isn't prompt tinkering. You'll be designing the delivery system itself the workflows, guardrails, and feedback loops that let a high-performing team move dramatically faster without sacrificing the engineering excellence we practice every day. Your work will directly accelerate a mission that matters: delivering workforce readiness to the nation's cyber warfighters.

Agentic development is the biggest shift in how software gets built since continuous delivery itself. Very few teams get to design and own that transformation from the ground up, backed by senior engineers who want it to succeed, in service of a mission that protects the people defending the nation. If you've been waiting for the role where AI engineering meets real delivery discipline and real impact, this is it.

About UKi

Since 1999, Ultimate Knowledge Institute has set the standard for cybersecurity training and readiness for the Department of Defense, federal agencies, and Fortune 500 companies. Today we're delivering a platform that builds and demonstrates true workforce and work-role readiness. Our platform identifies individual expertise gaps and builds adaptive, custom training plans to close those gaps for Federal U.S. Government, Defense, Intelligence Community, State/Local, and commercial customers. You'll be joining a newly forming AI engineering team inside a mature product engineering team, which means real users, real stakes, and a green field for how AI transforms the way we build.

What You'll Do

Build our agentic SDLC pipeline. Design, implement, and operate agentic workflows across the development lifecycle - planning, code generation, review, testing, documentation, and release that is all integrated with our GitOps and CI/CD infrastructure.

Level up developer experience. Bring modern AI integrations into the daily workflow of our engineering team: coding agents, automated review, intelligent test generation, and self-service tooling that removes friction and multiplies output.

Engineer grounded, trustworthy systems. Build retrieval-grounded and context-aware AI systems that produce reliable, verifiable results and design the evaluation harnesses that prove it.

Establish governance and guardrails. Define and implement the policies, human-in-the-loop checkpoints, audit trails, and security controls that let us adopt agentic AI responsibly in environments where trust is non-negotiable.

Formalize and scale. Turn what works into repeatable frameworks, playbooks, and internal platforms that extend agentic acceleration beyond engineering to the whole organization.

Champion the practice. Evangelize, teach, and support AI adoption across the team; you'll be a force multiplier, not a silo.

Why Now 

Agentic development is the biggest shift in how software gets built since continuous delivery itself - and very few teams get to design that transformation from a blank page, backed by senior engineers who want it to succeed, in service of a mission that protects the people defending the nation. If you've been waiting for the role where AI engineering meets real delivery discipline and real impact, this is it. 

Requirements

Required:

2-3+ years of hands-on experience building with AI/LLM systems in production settings.

2+ years designing and operating agentic workflows and pipelines including multi-step agent orchestration, tool use, evaluation, and governance.

Experience embedded in modern development teams practicing GitOps and CI/CD (required).

Working knowledge of grounded AI patterns: RAG, context engineering, structured outputs, and evaluation/observability for LLM systems.

Solid software engineering fundamentals in JavaScript/TypeScript and/or Python; comfort working in and around our stack (Angular/React frontends on Express web applications).

Genuine alignment with continuous delivery culture the Allspaw/Hammond, Phoenix Project (Kim) school of small batches, fast feedback, blameless learning, and operational excellence.

A self-starter's bias for action: you see an opportunity to accelerate the team and you build it, measure it, and share it.

Strong communication skills you can explain an agentic architecture to an engineer and its ROI to an executive.

Must be authorized to work in the United States; role is US-remote.
Nice to Have

Experience with agent frameworks and protocols (e.g., LangGraph/LangMem, Claude Agent SDK, MCP, OpenAI Agents) and AI coding tools (Claude Code, Copilot, Cursor).

Building developer platforms, internal tooling, or platform engineering / DevEx functions.

DORA-style delivery metrics and engineering analytics.

Familiarity with AI governance frameworks (NIST AI RMF) and secure SDLC practices.

Our Tech Environment 

Angular and React frontends on Express/Node.js web applications, delivered through GitOps and automated CI/CD pipelines. We practice continuous delivery: deploy often, automate everything, learn from every incident. You'll have wide latitude to introduce the agentic tooling and AI infrastructure this mission needs. 

Benefits

Base salary range: $150,000-$200,000, commensurate with experience, plus benefits. This range reflects current market rates for mid-level AI/agentic engineering talent in US-remote roles.