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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # AI Engineer, Agentic Systems - **Company:** SP Tech Resources Inc - **Location:** Columbus, OH, United States - **Experience:** Expert - **Salary:** $110,000.0 - $130,000.0 - **Contract:** Permanent contract - **Skills:** Java (Programming Language), Artificial Intelligence, Business Systems, Software Debugging, Java Web Services, Python (Programming Language), Software Engineering, Systems Architecture, Large Language Models, Multi-Agent Systems, Reliability of Systems, Generative AI, Backend, Kubernetes - **Published:** September 4, 2026 - **Apply:** https://www.careerjet.com/jobad/usc0fed258f1d4067ef84542ffccb37cf6 ## About the Role * 7+ years of software engineering experience, with demonstrated experience building and shipping production systems. * Hands-on production experience with agentic AI or GenAI applications, including deployment, monitoring, debugging, and operating agents at scale. * Strong Python engineering skills, with the ability to work effectively in production AI and agentic system environments. * Java experience or willingness to work daily within a Java service layer, especially where enterprise systems require integration with existing backend services. * Experience with agent frameworks and orchestration technologies, including LangChain and/or LangGraph. * Familiarity with production infrastructure for AI systems, including Kubernetes-based deployment environments. * Ability to explain shipped system architecture and failure modes, including what was deployed, how it was monitored, where it failed, and how issues were resolved. * Comfort working in a senior contract delivery model where the expectation is faster delivery and limited ramp-up investment. Preferred Qualifications * Experience with LangGraph as a production orchestration layer. * Experience with vLLM or comparable model-serving infrastructure. * Experience in regulated-industry or financial-services technology environments, especially where enterprise scale and production-path stakes are important. * Experience working with business stakeholders to deliver end-to-end AI use cases, not only platform or prototype work. * Ability to operate in an onsite or hybrid delivery model, especially in a market such as NYC where the attachment notes a deeper finance-AI contractor pool ## Description The Senior AI Engineer, Agentic Systems will design, build, deploy, and operate production-grade agentic AI systems that support enterprise-scale use cases. The role emphasizes shipped production experience, system reliability, orchestration, monitoring, debugging, and the ability to expose enterprise capabilities as tools or skills for LLM-powered agents. Core Responsibilities * Build and operate production agentic AI systems, including deployed, monitored, and debugged agents running at scale. * Own agentic use cases end-to-end, partnering directly with business stakeholders from problem definition through delivery and operational support. * Design orchestration patterns for autonomous or semi-autonomous agents using modern agent frameworks and production orchestration layers. * Develop enterprise capabilities as tools or skills for LLMs, enabling agents to interact with business systems and workflows in a controlled, scalable way. * Engineer reliable backend services for agentic workloads, with emphasis on Python-based development and integration with Java service layers where required. * Implement and support production infrastructure for AI workloads, including environments where Kubernetes and model-serving components such as vLLM may be part of the stack. * Evaluate and communicate system failure modes, including the ability to walk through shipped systems, operational issues, debugging approaches, and mitigation strategies. * Collaborate with vendor, engineering, and business teams to deliver solutions with limited ramp-up time, consistent with expectations for senior contract engineering talent. * Maintain a production-first engineering standard, ensuring the role does not over-index on framework familiarity at the expense of real deployment experience. ## Related Videos - [Developing the Backend with Stefan Lingler, CTO at Shpock](https://www.wearedevelopers.com/videos/100360-developing-the-backend-with-stefan-lingler-cto-at-shpock) - [Understanding Kubernetes in a visual way](https://www.wearedevelopers.com/videos/100085-understanding-kubernetes-in-a-visual-way) - [Your imaginations is (no longer) the limit: how Generative AI empowers people to be creative](https://www.wearedevelopers.com/videos/741-your-imaginations-is-no-longer-the-limit-how-generative-ai-empowers-people-to-be-creative) - [AI Agents Graph: Your following tool in your Java AI journey](https://www.wearedevelopers.com/videos/1550-ai-agents-graph-your-following-tool-in-your-java-ai-journey) - [Nest.js - TypeScript in the backend can also be clean](https://www.wearedevelopers.com/videos/1033-nest-js-typescript-in-the-backend-can-also-be-clean) - [Building AI Applications with LangChain and Node.js](https://www.wearedevelopers.com/videos/1512-building-ai-applications-with-langchain-and-node-js) ## 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) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [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) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [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)