About your role
As a Principal AI Engineer, you will design and deliver advanced generative artificial intelligence (AI) solutions that support scalable, production-ready intelligent applications across the enterprise. You will work with engineering, architecture, and product teams to build multi-agent systems, retrieval-augmented generation (RAG) pipelines, and cloud-native AI services that enable innovation and operational efficiency. Your work will help strengthen AI platform capabilities, improve solution reliability, and accelerate enterprise adoption of next-generation intelligent systems.
What you'll do
•Design and implement generative AI solutions using large language model orchestration frameworks such as LangChain, LangGraph, LlamaIndex, or similar technologies.
•Build and optimize multi-agent systems that coordinate intelligent task execution, reasoning, and workflow orchestration across enterprise applications.
•Develop retrieval-augmented generation (RAG) pipelines using embeddings, vector stores such as Weaviate, and data retrieval strategies that improve relevance and response quality.
•Build backend services and application interfaces using Python, FastAPI, Java, Spring Boot, or similar technologies to support scalable AI-driven applications.
•Design and support cloud-native AI solutions across Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform (GCP), including serverless and containerized deployment patterns.
•Collaborate with engineering and platform teams to integrate AI applications with data services, messaging systems, caching layers, and enterprise platforms such as Oracle, PostgreSQL, Apache Ignite, RabbitMQ, or similar technologies.
•Drive engineering best practices for observability, scalability, security, reliability, and operational readiness across AI and machine learning services.
•Provide technical leadership in solution design, architectural reviews, and implementation patterns that advance enterprise AI engineering standards.
•Evaluate and improve performance of AI applications through efficient use of data processing tools such as Apache Spark, Pandas, and related analytics or pipeline technologies.
•Responsibilities listed are not intended to be all-inclusive and may be modified as necessary.
Experience you'll need to have
•13+ years of experience in software engineering, AI engineering, machine learning engineering, or related technical disciplines supporting enterprise-scale applications.
•13+ years of experience developing production services using Python, Java, Spring Boot, FastAPI, or similar backend engineering frameworks.
•Experience with generative AI, multi-agent systems, large language model orchestration, and retrieval-augmented generation pipelines using tools such as LangChain, LangGraph, LlamaIndex, or similar frameworks.
•Experience with vector databases or semantic retrieval platforms such as Weaviate and with data integration patterns supporting AI application development.
•Experience deploying and operating cloud-native applications across AWS, Azure, GCP, Kubernetes, Docker, or serverless architectures.
•Experience working with relational and distributed data platforms such as Oracle, PostgreSQL, Apache Ignite, ElastiCache, RabbitMQ, Apache Spark, or similar technologies in scalable environments.
•Bachelor's degree or higher in Computer Science, Engineering, Data Science, Information Systems, or related field or equivalent combination of education, related experience and/or military experience.
Experience that would be great to have
•Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Engineering, or related field.
•Experience leading architecture and design decisions for enterprise AI platforms or intelligent application ecosystems.
•Experience in financial services, payments, or regulated technology environments.
•Experience with observability, evaluation, and governance practices for generative AI applications in production.
How you'll work
This role is on-site Monday through Friday. Fiserv considers in-person collaboration to be an essential part of this role as in-person office experiences help you with your overall onboarding experience and leads to stronger productivity.
