Full Stack Engineer

The Senior Full Stack Developer will design, build, and support modern capabilities for Crew Pay, a business-critical pay platform. This role combines hands-on application development with cloud-native engineering across AWS, event-driven services, streaming, data processing, and relational databases. The successful candidate will deliver secure, resilient, observable, and maintainable solutions while partnering with product owners, engineers, architects, quality engineering, DevOps, and business stakeholders. Design, develop, test, deploy, and support end-to-end full stack features for the Pilot Pay product Build cloud-native services using AWS ECS/Fargate, Lambda, SQS, SNS, S3, and RDS Develop event-driven workflows that consume, process, publish, and replay business events reliably Create and maintain Kafka producers, consumers, topics, schemas, error-handling patterns, and operational controls Develop and optimize Apache Spark jobs for scalable data transformation and pay-processing workloads Build responsive user experiences and secure APIs that provide clear business workflows, validation, and auditability Engineer for resilience through idempotency, retry strategies, dead-letter handling, failure recovery, and graceful degradation Implement automated unit, integration, component, regression, and end-to-end tests as part of CI/CD pipelines Improve production readiness through logging, metrics, tracing, alerting, runbooks, and root-cause analysis Participate in Agile delivery practices, code reviews, technical design discussions, estimation, and continuous improvement Collaborate with product and business partners to translate complex pay rules into understandable, testable, and maintainable solutions Mentor engineers and raise engineering standards for architecture, code quality, security, performance, and supportability Technical environment Cloud and compute: AWS ECS/Fargate and Lambda Messaging and events: Kafka, SQS, and SNS Data and storage: S3, RDS, Aurora, and SQL Data processing: Apache Spark and EMR Application development: Microservices, APIs, and modern web user interfaces Engineering: CI/CD, infrastructure-as-code, automated testing, and observability AI-enabled delivery: AI coding assistants, agents, and agentic workflows Success in this role Delivers reliable features that improve pay-processing accuracy, transparency, and operational efficiency Reduces production risk through strong engineering controls, automated validation, and actionable observability Improves delivery speed and code quality through reusable patterns, automation, and responsible use of AI-assisted engineering Takes ownership from design through production support and continuously improves the product and engineering system Qualifications What’s needed to succeed (Minimum Qualifications): Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related field, or equivalent practical experience 4+ years of professional software development experience, including ownership of production applications Strong back-end development experience using Java, Python, or a comparable enterprise language and framework Front-end development experience using a modern JavaScript or TypeScript framework such as React, Angular, or Vue Hands-on experience with RESTful APIs, microservices, distributed systems, and asynchronous processing Practical experience with AWS ECS/Fargate, Lambda, SQS, SNS, S3, and RDS Experience developing event-driven solutions using Kafka or a comparable streaming platform Experience building, troubleshooting, and optimizing Apache Spark jobs Strong knowledge of SQL, relational data modeling, transactions, and performance tuning Experience with infrastructure-as-code, CI/CD, source control, automated testing, and secure software development practices Demonstrated ability to diagnose complex production issues across applications, messaging, data, and cloud infrastructure layers Clear written and verbal communication skills, with the ability to work effectively across engineering and business teams What will help you propel from the pack (Preferred Qualifications): Experience supporting payroll, crew pay, financial, or other high-accuracy transaction-processing systems Experience with Amazon MSK, EMR or EMR Serverless, Aurora MySQL, container orchestration, and serverless architectures Knowledge of event schemas, data lineage, reconciliation, replay controls, and audit-trail design Experience applying observability, performance engineering, cost optimization, and operational automation in AWS Experience using AI-assisted development tools for requirements refinement, code generation, test creation, debugging, refactoring, documentation, or code review Experience creating AI agents or agentic workflows using tools or frameworks such as LangChain, LangGraph, Model Context Protocols, retrieval-augmented generation, or similar patterns Understanding of responsible AI practices, prompt and tool security, human-in-the-loop controls, evaluation, and production monitoring for AI-enabled solutions Experience working in a product-centric Agile environment with outcome-based delivery and shared operational ownership The base salary range/hourly rate listed is dependent on job-related, factors such as experience, education, and skills. This position is also eligible for bonus and/or long-term incentive compensation awards. You may be eligible for the following competitive benefits: medical, dental, vision, life, accident & disability, parental leave, employee assistance program, commuter, paid holidays, paid time off, 401(k) and flight privileges. LinkedIn