AI Workflow Engineer

Ultimate Knowledge Institute

AI Workflow Engineer designing and implementing workflows for agentic software delivery. Enhancing developer experiences with AI integrations and establishing governance for responsible AI use.

Posted 7/18/2026full-timeRemote • Florida, Maryland, Tennessee, Texas, Virginia • 🇺🇸 United StatesJuniorMid-Level💰 $150,000 - $200,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building and operating AI/LLM systems, designing agentic workflows, and implementing CI/CD practices. Strong ability to communicate complex concepts effectively across technical and executive audiences while fostering a culture of continuous delivery and operational excellence.

Highest-signal resume keywords

AI/LLM Systems DevelopmentAgentic Workflow DesignGitOps and CI/CD PracticesJavaScript/TypeScript and Python ProficiencyStrong Communication Skills

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

AI/LLM SystemsAgentic WorkflowsMulti-Step Agent OrchestrationGovernance and Security ControlsJavaScriptTypeScriptPythonAngularReactContinuous Delivery

Soft Skills

Strong CommunicationSelf-StarterTeam CollaborationTeaching and Evangelizing

Tools & Technologies

GitOpsCI/CD InfrastructureEvaluation HarnessesAutomated Review ToolsSelf-Service Tooling

Industry Keywords

Grounded AI PatternsContext EngineeringObservability for LLM SystemsOperational ExcellenceBlameless Learning

Tech Stack

Tools & technologies

AngularJavaScriptPythonReactSDLCTypeScript

About the role

Key responsibilities & impact

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.

Requirements

What you’ll need

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.

Benefits

Comp & perks

Base salary range: $150,000–$200,000, commensurate with experience, plus benefits.