Job Summary

The Java and Python Developer will lead and contribute to moderately complex technology initiatives involving software development, system enhancements, upgrades, deployments, and production support. The role requires strong hands-on experience with Java full-stack development, Kafka, Python, modern software engineering practices, and AI-assisted development. The developer will design, implement, test, debug, and document production-quality solutions while applying secure, scalable, and responsible engineering practices. The role will also provide technical guidance to less experienced engineers, collaborate with cross-functional stakeholders, and contribute to continuous improvements in system quality, performance, stability, scalability, and developer productivity.

Key Responsibilities
• Lead moderately complex initiatives and deliverables within technical domain environments.
• Contribute to large-scale technology strategy and planning activities.
• Design, code, test, debug, and document solutions for technology projects and programs, including upgrades and deployments.
• Review and resolve moderately complex technical challenges requiring in-depth evaluation of technologies and procedures.
• Lead projects and serve as an escalation point for technical issues.
• Provide guidance and direction to less experienced engineering staff.
• Develop and maintain production-quality applications using Java full stack, Python, Kafka, and technologies aligned with the team's technology stack.
• Apply AI-assisted development practices to improve engineering productivity, code quality, reliability, and delivery efficiency.
• Use approved AI-powered engineering tools for code generation, refactoring, code reviews, testing, documentation, observability, troubleshooting, and automation.
• Apply an AI-first engineering mindset while ensuring adherence to enterprise standards and responsible AI practices.
• Follow the end-to-end Software Development Lifecycle and Agile/DevOps delivery practices.
• Design and implement robust solutions while making informed architectural decisions within established guidelines.
• Participate in and lead code reviews and technical design discussions.
• Support deployments, upgrades, environment stability, and production operations, including on-call and incident support.
• Troubleshoot and resolve recurring and non-trivial technical issues using system telemetry, documentation, traditional debugging techniques, and AI-assisted analysis.
• Identify and implement improvements to service quality, performance, stability, scalability, and developer efficiency.
• Ensure security, compliance, risk, and data privacy controls are incorporated into design, development, and support activities.
• Apply appropriate safeguards when using AI tools with sensitive or enterprise data.
• Collaborate with engineers, product partners, peers, colleagues, and stakeholders to resolve technical challenges and achieve delivery objectives.
• Build strong domain expertise and identify AI use cases that can create measurable technical or business impact.
• Mentor junior engineers and share knowledge of technology, domain context, and effective use of AI engineering tools.
• Communicate technical status, risks, trade-offs, and recommendations clearly to team members and stakeholders.
• Contribute to continuous learning and adoption of emerging AI technologies and engineering patterns.

Required Qualifications
• 7+ years of Software Engineering experience, or equivalent experience demonstrated through work experience, training, military experience, or education.
• Approximately 7+ years of professional software engineering or application development experience with a proven track record of delivering production-quality systems.
• Strong hands-on experience with Java full stack, Kafka, Python, and frameworks aligned with the team's technology stack.
• Demonstrated ability to apply AI-assisted development practices at scale to improve engineering productivity, code quality, and reliability.
• Practical experience using AI-powered engineering tools such as code assistants, automated testing tools, documentation generators, observability and troubleshooting assistants, or internal AI platforms.
• Strong understanding of the end-to-end SDLC and hands-on experience working in Agile and DevOps delivery models.
• Advanced proficiency with source control systems, CI/CD pipelines, and modern development workflows, including AI-augmented reviews and automation.
• Experience supporting deployments, upgrades, environment stability, and production operations, including on-call or incident support.
• Strong foundational knowledge of databases, APIs, distributed systems, messaging platforms, and system integrations.
• Good awareness of security, risk, data privacy, compliance, and responsible AI usage.
• Ability to independently troubleshoot and resolve moderately complex technical issues using documentation, system telemetry, and AI-assisted insights.
• Demonstrated commitment to continuous learning, particularly emerging AI technologies and patterns relevant to software engineering.
• Strong communication and collaboration skills with engineers, product partners, and stakeholders.