Staff FullStack Engineer - Finance AI & Automation :: Onsite :: W2 Position ::

Role: Staff Full-Stack Engineer – Finance AI & Automation
Location: Boise, Idaho
Role Level: Staff / Senior Technical Leadership

Job Summary

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.

Key Responsibilities

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.

Required Technical Skills

• 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

Ideal Candidate Profile

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.