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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # AI Engineer - **Company:** Stellent IT LLC - **Location:** Saint Augustine, United States (Remote available) - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Microsoft Access, Java (Programming Language), Application Programming Interfaces (APIs), Artificial Intelligence, Applications Architecture, Microsoft Azure, Cloud Computing, Cloud Engineering, Code Review, Continuous Integration, Programming Tools, OAuth, Scrum Methodology, Release Management, Openid Connect, Software Engineering, Software Systems, Systems Integration, Management of Software Versions, Data Logging, Model Garden (Google Cloud), Design of Telemetry/logging Agents, Google Cloud, Enterprise Software Applications, GitHub Copilot, ReactJS, Large Language Models, Claude Code, Multi-Agent Systems, Spring-boot, Agentic-AI, Containerization, AI Platforms, Solid Principles, Information Technology, Google Gemini, Restful APIs, Network Server, Dynatrace, Microservices, Agent2Agent Protocol - **Published:** September 30, 2026 - **Apply:** https://www.dice.com/job-detail/6387cd35-4a9b-48f8-9d70-0b81e5e443b1 ## About the Role We are looking for a talented Senior AI Engineer to join our Engineering Frameworks Team. In this role, you will contribute to the design, development, integration, operationalization, and support of AI tools and platforms utilized by developers across the company to build solutions for their lines of business. This is a hands-on engineering role centered on Google Cloud Platform, Gemini and Vertex AI or comparable services, Claude Code, GitHub Copilot, MCP Servers, Java Spring Boot, and React.js. The ideal candidate will have direct, demonstrable experience building and integrating with AI tools and services, along with the ability to deliver reliable, secure, and maintainable solutions that accelerate software development and improve productivity across the organization., Bachelor's degree or equivalent work experience in computer science, engineering, artificial intelligence, or a related field, 5-7 years of experience in software engineering, platform engineering, AI engineering, or a related technical discipline Proven experience delivering high-quality software solutions in production environments Hands-on experience building or integrating AI, LLM, developer-platform, or automation capabilities Experience with cloud-based AI services platform such as Google Cloud Platform, Gemini, and Vertex AI or comparable model platforms Solid understanding of application architecture, integration patterns, APIs, and software design principles Experience developing Java REST APIs and services with Spring Boot and working knowledge of React.js or comparable front-end technologies Experience with secure API integrations and OAuth 2.0 / OpenID Connect authorization patterns, including service accounts, client credentials, or delegated user access Understanding of software development lifecycle, CI/CD, observability, reliability, security, privacy, and responsible AI practices Strong problem-solving skills, attention to detail, technical communication, and ability to collaborate effectively across teams Preferred Qualifications Hands-on experience using Claude Code and GitHub Copilot in an engineering workflow, including custom instructions, prompts, skills, plugins, or extensions Designing or implementing custom AI agents, reusable orchestration patterns, shared integrations, or reference implementations Building sequential, multi-agent, or deterministic graph-based agent workflows Building or integrating MCP servers and clients to expose tools, resources, or data sources to AI agents Enabling agent-to-agent communication using A2A or comparable protocols Experience with Google ADK, Spring AI, LangChain, LangChain4j, or similar LLM integration libraries and SDKs Experience with Gemini Agent Platform / Vertex AI capabilities such as model garden, model runtime, model gateway, or agent gateway Implementing model governance controls such as Google Cloud Platform Model Armor, cost controls, token limits, rate limits, and access policies Implementing logging, metrics, distributed tracing, token-utilization monitoring, and operational dashboards for AI services on Google Cloud Platform Exposure to containerization, microservices, and cloud-native application architecture Experience working with CI/CD pipelines in Harness and Azure DevOps, including automated build, test, security, and release workflows Familiarity with Agile/Scrum methodologies and development practices for shared platform capabilities Technical Skills Required AI Platforms: Google Cloud Platform, Gemini, Vertex AI, model garden, model runtime, model gateway, and agent gateway AI Engineering: custom agent design, sequential workflows, multi-agent systems, deterministic graph-based agents, and reusable orchestration patterns Developer Tools: Claude Code, GitHub Copilot, custom instructions, prompts, skills, plugins, and extensions Agent Integration: MCP servers and clients, tools, resources, data-source integrations, A2A patterns, and agent-to-agent communication Frameworks: Google ADK, Spring AI, LangChain, LangChain4j, or comparable AI/LLM integration libraries Application Development: Java, Spring Boot, REST APIs, React.js, microservices, and cloud-native application patterns Security and Governance: OAuth 2.0, OpenID Connect, service accounts, delegated access, model governance, Google Cloud Platform Model Armor, privacy, responsible AI, and access control Operations: CI/CD, Harness, Azure DevOps, logging, metrics, tracing, token utilization, performance, reliability, and incident support ## Description A senior role focused on developing and supporting AI platforms, developer tools, and agentic application capabilities. This position requires significant experience delivering high-quality software solutions, applying sound application and integration patterns, and contributing to the design of secure and scalable AI capabilities. The Senior AI Engineer will own significant technical work efforts end-to-end, collaborate with development teams and technical leaders, and help establish reusable patterns for building and operating custom agents throughout the company., Develop and maintain AI platforms, tools, and frameworks used by engineers across the company, including Claude Code, GitHub Copilot, MCP servers, plugins, skills, and agentic frameworks. Implement AI platform services, orchestration patterns, reference implementations, and shared integration components in collaboration with technical leads and architects. Design and deliver tools that support development of custom agents and workflows, including sequential, multi-agent, and deterministic graph-based solutions. Integrate and operationalize AI tools and services with cloud, security, development, and enterprise technology platforms. Build secure, scalable, reliable, observable, performant, and maintainable services for custom agents and AI tool integrations. Provide technical support and guidance to development teams building, deploying, and operating custom agents and MCP servers. Contribute to framework lifecycle practices, including versioning, release management, documentation, adoption, support, and continuous improvement. Implement logging, metrics, token-utilization monitoring, tracing, and other operational capabilities for AI services running on Google Cloud Platform. Apply enterprise security, privacy, responsible AI, access-control, governance, cost-management, and model-risk practices to AI solutions. Collaborate with development teams, security, and architecture to define requirements and deliver platform capabilities. Participate in code reviews, technical discussions, troubleshooting, and knowledge-sharing activities. 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