Software Engineer III- Java & AI

- Software Engineering: Design, build, test, and maintain high-quality software systems and services. Write clean, efficient, and maintainable code with a strong focus on correctness, scalability, reliability, and operational excellence. - Technical Ownership & Architecture: Lead the technical design and delivery of distributed, enterprise-scale systems and services. Contribute to architecture reviews, service decomposition strategies, API design, event-driven integrations, and data modeling decisions that support scalability, maintainability, and resilience. Own services end-to-end, including implementation, CI/CD automation, deployment, observability, operational health, and ongoing production support. - AI-Augmented Engineering: Use AI-assisted development tools such as GitHub Copilot, Claude, or similar technologies as part of the engineering workflow to improve productivity, accelerate development, and enhance testing and documentation quality. Review and validate AI-generated output with strong engineering judgment, correctness, security, and maintainability standards. - Code Quality & Testing: Maintain a high bar for code quality through thoughtful code reviews, automated testing, and strong engineering practices. Build deterministic and scalable test suites covering unit, integration, contract, and edge-case scenarios across distributed systems. - Reliability & Operations: Monitor and improve the reliability, availability, and performance of production services. Use telemetry, logging, metrics, and operational insights to proactively identify and resolve issues in high-scale environments. - Collaboration: Work closely with cross-functional teams across engineering, product, security, and business stakeholders to deliver complex features and systems iteratively with high quality and operational excellence. - Responsible AI: Apply responsible AI principles when integrating AI-powered capabilities into products or workflows, including considerations for privacy, transparency, auditability, governance, and compliance. - Documentation: Create and maintain clear technical documentation for systems, APIs, operational processes, and business-critical logic to support long-term maintainability and knowledge sharing. - Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience. - 4+ years of professional software engineering experience building and operating production-grade applications and services. - Strong proficiency in one or more modern programming languages such as Java, C#, Python, Go, or Kotlin. - Experience designing and operating distributed systems and microservices-based architectures. - Strong understanding of software engineering fundamentals, design patterns, testing methodologies, and system design principles. - Experience designing and consuming RESTful APIs and event-driven integrations. - Experience working with relational databases such as PostgreSQL or SQL Server in transactional or high-scale environments. - Experience with cloud platforms and containerized deployments using technologies such as Docker and Kubernetes. - Familiarity with CI/CD pipelines, version control systems (GitHub), and Agile development workflows. - Experience using AI-assisted engineering tools as part of a modern software development workflow. - Experience building and operating workloads on AWS, Azure, or GCP. - Experience with observability, monitoring, and production operations in large-scale distributed systems. - Experience implementing automated testing strategies across unit, integration, and contract testing layers. - Experience building systems in compliance-sensitive or business-critical domains. - Experience integrating AI-powered capabilities such as LLM APIs, intelligent automation, or agentic workflows into production applications. - Understanding of responsible AI principles, including governance, explain ability, privacy, and risk mitigation. - Strong communication and collaboration skills with the ability to work effectively across technical and non-technical teams. - Demonstrated ability to drive projects independently and influence technical direction across teams.