Principal, AI Engineer

Overview

Design and deliver advanced generative AI solutions that support scalable, production-ready intelligent applications across the enterprise, working with engineering, architecture and product teams on multi-agent systems, RAG pipelines and cloud-native AI services.

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.

What you'll need

• 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.

Nice 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.

Details

• On-site, Monday through Friday.