Note: The job is a remote job and is open to candidates in USA. FICO is a leading analytics and decision management company that empowers businesses and individuals with data-driven insights. The Senior or Lead Backend Engineer will integrate robust data engineering with next-generation AI capabilities, designing and maintaining scalable backend systems and data pipelines that enhance FICO's 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
Skills
- 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
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