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# AI Engineer

- **Company:** COMPUTER VISIONARIES, INC.
- **Location:** Dallas, TX, United States
- **Experience:** Experienced
- **Contract:** Permanent contract
- **Skills:** JavaScript (Programming Language), Application Programming Interfaces (APIs), Artificial Intelligence, Computer Vision, Software as a Service, Continuous Integration, Python (Programming Language), Knowledge-Based Systems, OpenAI, Software Deployment, Software Engineering, Systems Integration, TypeScript, Web Application Frameworks, Test-Driven Development (TDD), Retrieval-Augmented Generation, Large Language Models, Multi-Agent Systems, Prompt Engineering, Llamaindex, Agentic-AI, CrewAI, Claude, Google Gemini, Restful APIs, Model Context Protocol
- **Published:** October 23, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=e8dfcc1ecd0da931

## About the Role

* 2-5 years of software engineering experience with a demonstrated track record of production deployments.
 * Experience using AI agents, coding assistants, or agentic frameworks to deploy production-grade code at a company or for a client.
 * Experience with spec-driven and test-driven development workflows.
 * Ability to critically evaluate agent-produced code and identify hallucinations, security gaps, and quality issues before deployment.
 * A strong focus on security, scalability, repeatability, and well-documented deliverables.
 * Strong written and verbal communication skills.
 * Comfort presenting technical deliverables and progress directly to clients.
 * Familiarity with modern web frameworks, RESTful APIs, and CI/CD workflows.
 * Ability to work a hybrid schedule from our Dallas offices in the Galleria / Addison area., * Experience building or implementing agentic knowledge systems, including RAG pipelines, agent memory systems, or wikis designed for shared human-agent use.
 * Hands-on experience integrating computer vision technologies into production systems.
 * Familiarity with LLM APIs, including Anthropic Claude, Google Gemini, OpenAI, or equivalent, and prompt engineering patterns.
 * Experience with agentic frameworks such as LangChain, LlamaIndex, or CrewAI, and integration protocols such as Model Context Protocol (MCP).
 * Prior experience in consulting, managed services, or client-embedded delivery.
 * Experience working in regulated environments or with compliance frameworks such as FedRAMP, SOC 2, or HIPAA.
 * Proficiency in Python, TypeScript/JavaScript, or both.

THE MINDSET WE'RE LOOKING FOR

We're hiring for technical skills and a way of thinking. The right candidate sees AI agents as teammates. When a problem lands on your desk, your instinct is to consider which agent can help tackle it, whether that means writing tests, researching an API, scaffolding a service, or reviewing a pull request.

You're curious, you ship, and you hold yourself to a high standard of quality even when agents are doing the heavy lifting.

## Description

We're looking for a mid-level AI Engineer who uses AI agents as a personal force multiplier to architect, test, document, and ship production-grade solutions for our clients.

You'll work on client engagements across industries, translating business requirements into agentic workflows, deploying intelligent systems, and ensuring every deliverable meets enterprise standards for security, scalability, and repeatability.

You'll also regularly interact with clients, explaining technical deliverables clearly and confidently. You'll work alongside senior engineers and engagement leads in small, fast-moving teams where every team member has an outsized impact., * Design, build, and deploy agentic AI solutions, from single-agent workflows to multi-agent orchestration, with agents serving as core functionality, user interfaces, or both.

 * Use spec-driven and test-driven development practices with AI agents to produce reliable, secure, tested, and well-documented code.
 * Identify and bring new applications of AI to our clients' businesses.
 * Evaluate agent-produced code for quality, security, and alignment with client requirements.
 * Build and integrate client-facing applications that embed AI capabilities where users work, replacing manual processes and legacy SaaS tools.
 * Contribute to agentic knowledge systems, including RAG pipelines, agent memory architectures, and shared human-agent wikis.
 * Document architectures, decision criteria, integration patterns, and deployment configurations to support knowledge transfer.