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.