FICO

analytics software

Senior/Lead-BackendEngineer/DataEngineer-AIEngineering

$140–140k United States FULL TIME Remote Friendly
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Senior candidates.

The Brief

“Senior/Lead - Backend Engineer/Data Engineer - AI Engineering at FICO. Skills: Backend Engineering, Data Engineering, Applied AI, Large Language Models. Design and deploy scalable backend systems. Build high-quality solutions for data ingestion”

What You'll Achieve.

making a lasting impact on FICO's platform; seamlessly integrate applied AI capabilities; ensuring reliable, high-throughput data flow; support high-volume, low-latency workloads; ensure system reliability, security, and scalability; support FICO's analytics and decisioning solutions at scale

Industry & Context.

analytics software
Problems you'll solve

problem-solving skills

What They're Looking For.

Must Have

7+ years of experience in backend or data engineering, coding skills in Python, Go, Java, or equivalent languages, Hands-on experience with big data frameworks (e.g., Apache Spark, Kafka, Hadoop), understanding of both relational and NoSQL databases, Experience with cloud platforms (AWS, GCP, or Azure), container orchestration tools such as Docker and Kubernetes, Proven ability to design, build, and maintain scalable, production-grade backend systems, Solid experience with testing frameworks (including A testing), performance optimization, production monitoring/observability practices, Demonstrated experience integrating AI/ML solutions into production systems, working with Large Language Models (LLMs), problem-solving and communication skills

Nice to Have

An advanced degree is a plus, Experience with Retrieval-Augmented Generation (RAG) architectures, familiarity with vector databases (e.g., Pinecone, Weaviate, pgvector)

What You'll Do.

Design and deploy scalable backend systems

Build high-quality solutions for data ingestion

Design and implement LLM-powered solutions

Develop sophisticated prompting strategies

Partner with data scientists

Optimize distributed architectures

Implement advanced monitoring techniques

Define and evolve architectural patterns

Lead and mentor engineering team members

How You'll Work.

Team & Collaboration

collaborate with a high-caliber team; Partner with data scientists, ML engineers, and product teams; collaborate effectively across disciplines

Communication Scope

communication skills

Full Job Description

**FICO (NYSE: FICO)** is a leading global analytics software company, helping businesses in 100+ countries make better decisions. Join our world-class team today and fulfill your career potential! **The Opportunity** _" As a Senior or Lead Backend Engineer on our Applied AI team, you will be at the forefront of integrating robust data engineering with next-generation AI capabilities. You will design, build, and maintain scalable backend systems and data pipelines that power critical functions across our platform — from fraud investigation and decision automation to process optimization. In this role, you will champion high data quality, system reliability, and stringent governance across all AI-driven initiatives, making a lasting impact on FICO's platform. This is an opportunity to collaborate with a high-caliber team and drive meaningful innovation through your deep expertise in backend engineering and applied AI." \- VP, AI Engineering_ **What You 'll Contribute** * 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,

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