Full stack dev Python w/ AWS

Compunnel

$110K — $130K *
Information Technology
5 - 7 years of experience
Job Overview by Ladders

Qualifications

  • 7-10+ years of AWS application development experience
  • Strong hands-on experience with Python and AWS
  • Solid understanding of APIs, integrations, and distributed systems
  • Experience with data engineering or developing data-focused applications
  • Background in building user interfaces or full-stack applications
  • Familiarity with fraud and case management systems
  • Experience with AI-assisted development tools and practices

Responsibilities

  • Design, develop, and maintain scalable applications for fraud case management
  • Develop cloud-native services, APIs, and user experiences
  • Build resilient and secure solutions meeting enterprise requirements
  • Participate in technical design discussions and contribute to architecture
  • Lead development of complex features and platform capabilities
  • Perform code reviews and mentor engineers on best practices
  • Establish patterns for testing, automation, and DevSecOps

Benefits

  • Hybrid work arrangement
  • Opportunities for professional growth in a cutting-edge technology environment
  • Collaboration with cross-functional teams to drive innovation
  • Exposure to AI technologies within a dynamic industry
  • Significant impact on fraud operations and investigative workflows
Full Job Description
Job Summary

The Full Stack Developer will design, develop, and maintain scalable applications supporting a unified fraud case management ecosystem. The role requires strong Python and AWS development experience combined with data and user-interface skills. The engineer will develop cloud-native services, APIs, integrations, and user experiences supporting fraud operations and investigative workflows while contributing to architecture, technical excellence, AI-enabled development, and platform modernization.

Key Responsibilities
• Design, develop, and maintain scalable applications supporting a unified fraud case management ecosystem.
• Develop cloud-native services, APIs, integrations, and user experiences supporting fraud operations and investigative workflows.
• Build resilient and secure solutions that meet enterprise performance, availability, and compliance requirements.
• Participate in technical design discussions and contribute to architecture decisions.
• Lead development efforts for complex features and platform capabilities.
• Perform code reviews and mentor engineers on engineering best practices.
• Establish patterns for testing, observability, resiliency, automation, and DevSecOps.
• Partner with architects and technical leads to improve engineering standards.
• Work closely with teams supporting existing fraud and case management applications.
• Participate in solution planning and dependency management across multiple engineering teams.
• Help drive technical alignment supporting the long-term platform strategy.
• Utilize AI-assisted development tools to improve coding efficiency, testing, documentation, and troubleshooting.
• Identify opportunities for AI-driven capabilities within fraud operations and investigator workflows.
• Experiment with emerging AI technologies and contribute recommendations for responsible adoption.
• Share knowledge and best practices that help teams leverage AI effectively and securely.
• Partner with product owners and business stakeholders to understand investigative workflows and operational needs.
• Contribute to iterative delivery of capabilities that improve investigator experience and operational effectiveness.
• Support platform enhancements for future regional expansion and evolving business requirements.

Required Qualifications
• 7-10+ years of AWS application development experience.
• Strong hands-on experience with Python and AWS.
• Strong understanding of APIs, integrations, distributed systems, and modern application architectures.
• Experience with data engineering or data-focused application development.
• Experience developing user interfaces or full-stack applications.
• Experience with fraud and case management systems.
• Experience with AI-assisted development tools and engineering practices.
• Strong understanding of cloud-native application development.
• Strong communication and collaboration skills.

Preferred Qualifications
• Experience with Node.js and APIs.
• Experience with fraud prevention, fraud operations, or fraud technology.
• Experience with enterprise-scale fraud platforms and investigative workflows.
• Experience with DevSecOps, observability, resiliency, and automated testing.
• Experience with AI-driven capabilities for fraud operations.

Location
• Malvern, PA
• Charlotte, NC
• Plano, TX
• Scottsdale, AZ
• Hybrid work arrangement.

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