Senior/ Lead - Backend Engineer - Applied Engineering

FICO is a leading analytics and decision management company that empowers businesses and individuals around the world with data-driven insights. As a Senior or Lead Backend Engineer on the Applied AI team, you will design, build, and maintain scalable backend systems and data pipelines to integrate AI capabilities into FICO's analytics platform.

Responsibilities:

• Design and deploy scalable backend systems and data pipelines that seamlessly integrate applied AI capabilities into FICO's analytics and decision management platform
• Build high-quality solutions for data ingestion, transformation, and storage, ensuring reliable, high-throughput data flow for real-time analytics
• Design and implement LLM-powered solutions for decision automation, fraud investigation, and process automation within FICO's platform
• Develop sophisticated prompting strategies and Retrieval-Augmented Generation (RAG) architectures tailored to high-stakes, mission-critical applications
• Partner with data scientists, ML engineers, and product teams to develop microservices and APIs that enable intelligent, data-driven decision-making
• Optimize distributed architectures and implement real-time processing frameworks to support high-volume, low-latency workloads
• Implement advanced monitoring, testing, and performance optimization techniques to ensure system reliability, security, and scalability
• Define and evolve architectural patterns that support FICO's analytics and decisioning solutions at scale
• Lead and mentor engineering team members, promoting best practices in software development, data engineering, AI integration, and systems design

Requirements:

• 5+ years of experience in backend or data engineering, with a demonstrated track record of delivering complex, large-scale production systems
• Strong coding skills in Python, Go, Java, or equivalent languages, with a commitment to clean, maintainable, and well-tested code
• Hands-on experience with big data frameworks (e.g., Apache Spark, Kafka, Hadoop) and a strong understanding of both relational and NoSQL databases
• Experience with cloud platforms (AWS, GCP, or Azure) and container orchestration tools such as Docker and Kubernetes
• Proven ability to design, build, and maintain scalable, production-grade backend systems with a focus on reliability and performance
• Solid experience with testing frameworks (including A/B testing), performance optimization, and production monitoring/observability practices
• Demonstrated experience integrating AI/ML solutions into production systems, including working with Large Language Models (LLMs) and related techniques
• Strong problem-solving and communication skills, with the ability to mentor engineers, influence technical direction, and collaborate effectively across disciplines
• Bachelor's or Master's degree in Computer Science, Engineering, or a related field
• Experience with Retrieval-Augmented Generation (RAG) architectures and familiarity with vector databases (e.g., Pinecone, Weaviate, pgvector) is strongly preferred
• An advanced degree is a plus but not required