Software Engineering – Senior Engineer

FICO

1d•$122,500 - $192,500

About The Position

The myFICO engineering team builds web applications for FICO Scores consumer-facing business. We are increasingly using AI and Machine Learning for what we build and how we build, allowing our engineers to work faster and more efficiently. We spend a lot of time building delightful customer experiences on mobile apps, responsive web applications hosted on the AWS cloud, backed by loads of automation, monitoring, and strong cyber-security measures.

Requirements

Extensive hands-on experience with core Java, Spring Boot, and microservices architecture, with deep proficiency in deploying and operating services on AWS with Docker and Kubernetes.
Hands-on experience integrating LLM APIs (Anthropic, Bedrock, OpenAI) into production Java services.
Working knowledge of both SQL (PostgreSQL, SQL Server, MySQL) and NoSQL (DynamoDB, MongoDB, Cassandra) databases, including when to choose which.
Strong foundation in application security: encryption, authentication, authorization, and secure API design.
Proven experience tuning high-throughput, low-latency systems for performance and reliability and fluency with event-driven architectures and asynchronous messaging patterns (Kafka, SQS, EventBridge, or similar).
Experience with modern engineering practices: CI/CD pipelines, infrastructure as code, and automated testing at multiple levels (unit, integration, contract).
Proven experience with high-traffic consumer facing platform experience and a strong advocate for rigorous coding standards and a quality-first mindset — clean, secure, well-tested code.
Exceptional communication skills; able to articulate design tradeoffs with architects, engineers, and product partners.
Bachelor's or Master's degree in Computer Science or a related field (or equivalent work experience in relevant industry); AWS certifications a plus.

Responsibilities

Design, build, and operate secure, scalable Java microservices that power the myFICO.com platform — from concept through production.
Ship LLM-powered features (RAG pipelines, agentic workflows, tool-use patterns) with the same engineering rigor - observability, evals, and guardrails - you'd apply to any critical service.
Use AI-assisted development tools (Claude Code, Cursor, GitHub Copilot) to accelerate delivery, while exercising the judgment to review, refactor, and reject generated output where appropriate.
Drive design discussions and code reviews, raising the bar for code quality, test coverage, and architectural clarity.
Partner with product management, InfoSec, and platform teams to translate business requirements into compliant, effective technical solutions.
Identify and resolve performance and scalability bottlenecks through profiling, refactoring, and architectural improvements.