7+ years of Software Engineering experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education
Desired Qualifications:
Approximately 7+ years of professional experience in software engineering or application development 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
7+ years of Demonstrated ability to apply AI‑assisted development practices at scale to improve engineering productivity, code quality, and reliability
7+ years of Practical experience using AI‑powered engineering tools (e.g., code assistants, automated testing tools, documentation generators, observability and troubleshooting assistants, or internal AI platforms)
7+ years of Solid understanding of the end‑to‑end software development life cycle (SDLC) and hands‑on experience working in Agile / DevOps delivery models
7+ years of Advanced proficiency with source control systems, CI/CD pipelines, and modern development workflows, including AI‑augmented reviews and automation
7+ years of Experience supporting deployments, upgrades, environment stability, and production operations, including on‑call or incident support
7+ years of 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, with the ability to apply these principles in design and implementation
Ability to independently troubleshoot and resolve moderately complex technical issues, leveraging documentation, system telemetry, and AI‑assisted insights
7+ years of Demonstrated commitment to continuous learning, especially emerging AI technologies and patterns relevant to the engineering domain
Strong communication skills with the ability to collaborate effectively with engineers, product partners, and stakeholders, and to mentor junior team members
Job Expectations:
Lead and contribute to moderate to high‑complexity technology initiatives, including new feature development, system enhancements, upgrades, and deployments
Design, implement, test, debug, and document robust solutions, making informed architectural decisions within established guidelines
Apply an AI‑first engineering mindset, proactively using approved AI tools for code generation, refactoring, reviews, testing, troubleshooting, and documentation while ensuring compliance with enterprise standards
Drive adherence to engineering best practices, design patterns, coding standards, and responsible AI and data‑usage policies
Identify, propose, and help implement improvements to service quality, performance, stability, scalability, and developer efficiency
Independently investigate and resolve recurring and non‑trivial technical issues, leveraging both traditional debugging techniques and AI‑assisted analysis, and lead resolution efforts to meet SLAs
Ensure security, compliance, and risk controls are embedded into design, development, and support activities, including appropriate handling of sensitive data when using AI tools
Actively participate in and lead code reviews and technical design discussions, providing clear, constructive feedback
Mentor and support junior engineers, sharing knowledge on technology, domain context, and effective use of AI tools
Build strong domain expertise in the assigned business area and help identify AI use cases that create measurable technical or business impact
Communicate technical status, risks, trade‑offs, and recommendations clearly to team members and stakeholders
Demonstrate ongoing growth in technical leadership, decision‑making, system ownership, and responsible AI usage
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