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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # AI-Native Forward Deployed Engineer - **Company:** CIS Technologies Inc. - **Location:** McKinney, TX, United States (Remote available) - **Experience:** Expert - **Contract:** Temporary contract - **Skills:** Java (Programming Language), Artificial Intelligence, Amazon Web Services, Microsoft Azure, C Sharp (Programming Language), Code Review, Continuous Integration, Cursor (Graphical User Interface Elements), Python (Programming Language), Node.Js, Systems Development Life Cycle, Systems Integration, TypeScript, AI Infrastructure, Google Cloud, GitHub Copilot, Large Language Models, Multi-Agent Systems, Kubernetes, Infrastructure Automation Frameworks, Docker, Golang - **Published:** August 31, 2026 - **Apply:** https://www.dice.com/job-detail/f927852f-553f-45d2-96df-ae5ef4a06192 ## About the Role * 8+ years building and shipping production software, with recent hands-on delivery experience. * Demonstrated use of AI coding agents as part of your daily workflow Claude Code, Cursor, GitHub Copilot, or equivalent. * Practical experience with LLM application patterns: prompting and context engineering, RAG, tool use, evaluation, and observability. * Strong proficiency in at least one of Python, TypeScript, C#, Java, or Node, and comfort reading the others. * Production experience on at least one major cloud (Azure, AWS, or Google Cloud) with containers and CI/CD. * A track record of advising and influencing engineering teams you can point to people and teams who work differently because of you. * Consulting-grade communication: you can hold a room of skeptical senior engineers and a room of executives on the same day. * Willingness to travel to customer sites as the engagement requires., * Experience with agent frameworks such as LangGraph, CrewAI, AutoGen, Semantic Kernel, or the OpenAI Agents SDK. * Experience building MCP servers or integrations. * Prior consulting, professional services, or forward-deployed engineering experience in an enterprise environment. * Experience driving a developer-productivity, platform-adoption, or DevEx transformation across an organization. * Familiarity with enterprise constraints on AI: data residency, IP and licensing, secure SDLC, and model governance. Technologies You May Work With: * AI development tools: Claude Code, Cursor, GitHub Copilot, Astra * Models: Anthropic Claude, OpenAI, Gemini * Agent frameworks: LangGraph, CrewAI, AutoGen, Semantic Kernel, OpenAI Agents SDK * AI infrastructure: MCP, RAG, vector databases, evaluation, observability * Languages: Python, TypeScript, C#, Java, Go * Cloud: Azure, AWS, Google Cloud * Platform: Kubernetes, Docker, CI/CD, Infrastructure as Code ## Description * Deliver with the customer * Embed with enterprise customer teams as a hands-on senior engineer and trusted technical advisor. * Build AI-native applications and agentic workflows, including multi-agent systems, MCP integrations, and RAG pipelines. * Prototype in hours, then productionize what works with the evaluation, observability, and CI/CD rigor production demands. * Turning one customer's innovation into a reusable capability the rest of our customers can adopt. Consult on AI-native adoption: * Advise engineering leadership on AI-native adoption strategy, tooling selection, and rollout sequencing. * Assess the customer's current development practices and produce a prioritized adoption roadmap with measurable outcomes. * Define the standards that make AI-assisted development safe: code review norms, prompt and context management, testing and evaluation, security and IP guardrails. * Navigate resistance and organizational inertia; build coalitions with staff engineers, architects, and delivery managers. ## Related Videos - [AI Agents & Agentic AI](https://www.wearedevelopers.com/videos/2017-ai-agents-agentic-ai) - [Go with the Flow: Stop the Leaks Before Your Memory's a Waterfall!](https://www.wearedevelopers.com/videos/100073-go-with-the-flow-stop-the-leaks-before-your-memory-s-a-waterfall) - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [Stop using Node.js like in 2020! What changed and what you can do today with Node.js](https://www.wearedevelopers.com/videos/100011-stop-using-node-js-like-in-2020-what-changed-and-what-you-can-do-today-with-node-js) - [Building AI Applications with LangChain and Node.js](https://www.wearedevelopers.com/videos/1512-building-ai-applications-with-langchain-and-node-js) - [AI Killed DevOps... What Now? - Lee Faus](https://www.wearedevelopers.com/videos/1759-ai-killed-devops-what-now-lee-faus) ## Related Articles - [What is Agentic Programming and Why Should Developers Care?](https://www.wearedevelopers.com/magazine/625-what-is-agentic-programming-and-why-should-developers-care) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [From Prototype to Production: Build AI Agents with This Free 4-Course Learning Path](https://www.wearedevelopers.com/magazine/655-from-prototype-to-production-build-ai-agents-with-this-free-4-course-learning-path) - [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering) - [Everything a Developer Needs to Know About MCP with Neo4j](https://www.wearedevelopers.com/magazine/604-everything-a-developer-needs-to-know-about-mcp-with-neo4j)