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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior AI Platform Engineer - **Company:** U.S. Bank, National Association - **Location:** Hopkins, MN, United States - **Experience:** Expert - **Salary:** $124,355.0 - $146,300.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Amazon Web Services, Automation of Tests, Microsoft Azure, Cloud Computing, Cloud Engineering, Code Review, Continuous Integration, Data Governance, Distributed Systems, Monitoring of Systems, Python (Programming Language), Machine Learning, Performance Tuning, Secure Coding, Software Engineering, Data Logging, Delivery Pipeline, Large Language Models, Prompt Engineering, Software Security, Generative AI, Containerization, AI Platforms, Kubernetes, Infrastructure Automation Frameworks, Information Technology, Bicep, Virtual Agents, Terraform, Docker, Microservices - **Published:** June 18, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=2c58ef67d04646b2 ## About the Role Do you have experience in System security?, * Bachelor's degree, or equivalent work experience * Five to six years of relevant experience, * Bachelor's degree in Computer Science, Engineering, or related field * 7 - 9 years of experience in software or platform engineering * 2+ years hands-on experience with GenAI systems, including LLMs and RAG architectures and vector databases * Understanding of agentic AI concepts and exposure to frameworks such as LangChain or LangGraph * Experience with cloud platforms (Azure and/or AWS) * Knowledge of distributed systems and scalable application design * Proficiency in Python development * Experience with Docker, Kubernetes, and Infrastructure as Code tools * Experience deploying GenAI or ML solutions in production environments * Familiarity with observability and monitoring tools * Understanding of AI governance, compliance, and security practices * Experience in financial services or other regulated industries is a plus Core Competencies Technical Execution * Applies strong software engineering fundamentals to build production-grade systems * Delivers reliable, scalable, and maintainable GenAI solutions Systems Thinking * Understands distributed systems and cloud-native architectures * Designs for scalability, performance, and resiliency Learning & Innovation * Keeps pace with evolving GenAI technologies and frameworks * Continuously improves solution quality through experimentation Collaboration & Delivery * Works effectively across engineering and product teams * Delivers against commitments with strong ownership and accountability ## Description The Senior Engineer (Generative AI) is responsible for designing, developing, and deploying scalable Generative AI (GenAI) solutions within an enterprise environment. This role requires strong hands-on expertise in LLM-based applications, GenAI architectures, and modern cloud-native engineering practices. The position partners closely with cross-functional teams to build production-ready AI systems that meet enterprise standards for scalability, security, and reliability., 1. GenAI Solution Development * Develop and implement GenAI applications leveraging: + Large Language Models (LLMs) + Retrieval-Augmented Generation (RAG) architectures + Prompt engineering techniques + Agentic AI concepts and workflows * Build intelligent pipelines using frameworks such as LangChain, LangGraph, and Microsoft Foundry Agent Service * Evaluate solution performance, accuracy, and scalability of GenAI implementations 2. GenAIOps & Lifecycle Support * Contribute to the end-to-end GenAI lifecycle, including: + Solution design and development + Integration and deployment + Performance tuning and optimization * Support secure deployment, horizontal scaling, and operational stability of GenAI workloads * Assist in implementing monitoring, logging, and observability practices for production environments 3. Cloud, Platform & Scalability Engineering * Develop and deploy GenAI systems across cloud platforms (Azure and AWS) * Contribute to distributed system design for scalable AI workloads * Utilize modern infrastructure practices: + Containerization (Docker) + Orchestration (Kubernetes) + Infrastructure as Code (Terraform, ARM/Bicep) * Ensure solutions meet enterprise expectations for availability, performance, and security 4. Software Engineering & Delivery Excellence * Develop scalable applications using Python and microservices-based architectures * Apply secure coding standards and proper data handling practices for enterprise, regulated environments * Contribute to CI/CD pipelines, automated testing, and deployment workflows * Participate in code reviews and adhere to engineering best practices ## Related Videos - [Infrastructure as Code: The Developer's Secret Weapon](https://www.wearedevelopers.com/videos/1221-infrastructure-as-code-the-developer-s-secret-weapon) - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [Back(end) to the Future: Embracing the continuous Evolution of Infrastructure and Code](https://www.wearedevelopers.com/videos/440-back-end-to-the-future-embracing-the-continuous-evolution-of-infrastructure-and-code) - [Beyond GPT: Building Unified GenAI Platforms for the Enterprise of Tomorrow](https://www.wearedevelopers.com/videos/1525-beyond-gpt-building-unified-genai-platforms-for-the-enterprise-of-tomorrow) - [Implementing Feature Environments with AWS and Terraform](https://www.wearedevelopers.com/videos/531-implementing-feature-environments-with-aws-and-terraform) - [Docker build without Docker](https://www.wearedevelopers.com/videos/100114-docker-build-without-docker) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Got AI ideas but no money? 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