> Markdown version of [/jobs/ext/3747639-staff-fullstack-engineer-finance-ai-automation-onsite-w2-position](https://www.wearedevelopers.com/jobs/ext/3747639-staff-fullstack-engineer-finance-ai-automation-onsite-w2-position). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Staff FullStack Engineer - Finance AI & Automation :: Onsite :: W2 Position - **Company:** Trebecon LLC - **Location:** Boise, ID, United States - **Experience:** Expert - **Contract:** Contract - **Skills:** Java (Programming Language), Application Programming Interfaces (APIs), Artificial Intelligence, Application Performance Management, Microsoft Azure, Cloud Computing, Cloud Engineering, Continuous Integration, DevOps, Distributed Systems, Python (Programming Language), Machine Learning, OpenAI, Microsoft Copilot, Software Deployment, TypeScript, Workflow Management Systems, Enterprise Search, Enterprise Software Applications, Spring Cloud, ReactJS, Retrieval-Augmented Generation, Large Language Models, Multi-Agent Systems, Prompt Engineering, Spring-boot, Generative AI, Backend, Agentic-AI, Fastapi, Build Management, Microsoft Copilot Studio, Containerization, AI Platforms, AngularJS, Kubernetes, Front End Software Development, Azure AI, Artificial Intelligence Governance, Restful APIs, Human in the Loop, Docker, Microservices - **Published:** October 15, 2026 - **Apply:** https://www.dice.com/job-detail/3044f915-619a-4530-9a6d-6bab275bd01c ## About the Role Client is seeking an experienced Staff Full-Stack Engineer to design, develop, and scale enterprise AI and automation solutions for Finance. The ideal candidate will have strong full-stack development skills, hands-on Generative AI and Agentic AI experience, and expertise in cloud engineering and enterprise architecture. The candidate should be capable of independently taking AI initiatives from concept through development, integration, and production deployment., * Programming: Python, TypeScript * Frontend: React or Angular * Backend: FastAPI, Java, Spring Boot * Generative AI: LLM integration, RAG, prompt engineering * Agentic AI: AI agents, tool calling, workflow orchestration, multi-agent systems * Azure AI: Azure OpenAI, Azure AI Foundry, Microsoft Copilot, Copilot Studio * Cloud & DevOps: Azure, Docker, Kubernetes, CI/CD * Architecture: Enterprise design patterns, distributed systems, APIs, microservices, security, and scalability Preferred Candidate Background Candidates with experience in any of the following areas are preferred: * Microsoft AI and Azure AI projects * Enterprise Generative AI transformations * AI platform engineering teams * Internal developer platform teams * Product engineering organizations, The ideal candidate is a highly experienced technical engineer with strong full-stack development expertise, practical experience delivering production-ready AI solutions, and the ability to independently drive enterprise AI initiatives from design to deployment. ## Description 1. AI Engineering * Design and develop Generative AI and LLM-powered applications. * Build Retrieval-Augmented Generation (RAG) solutions. * Develop AI agents, multi-agent systems, and intelligent workflows. * Implement human-in-the-loop processes and AI guardrails. * Integrate AI models with enterprise applications and systems. 2. Full-Stack Development * Develop frontend applications using React, Angular, and TypeScript. * Build backend services using Python, FastAPI, Java, and Spring Boot. * Develop scalable APIs, microservices, and enterprise integrations. * Ensure application performance, security, and maintainability. 3. Cloud & Platform Engineering * Build and deploy cloud-native applications on Azure. * Use Docker and Kubernetes for containerization and orchestration. * Implement CI/CD pipelines, monitoring, and reliability practices. * Design event-driven architectures and scalable distributed systems. 4. Enterprise AI Platforms * Work with Azure OpenAI and Azure AI Foundry. * Integrate Microsoft Copilot and Copilot Studio. * Implement enterprise search capabilities and AI security guardrails. * Ensure solutions meet enterprise security, scalability, and governance requirements.