Java Technical Lead

At InRhythm, we are redefining modern software engineering through our AI-Driven Development Lifecycle (AI-DLC)—a spec-driven, agentic software delivery methodology powered by AI coding assistants such as Claude Code, GitHub Copilot, Cursor AI, Windsurf, Gemini Code Assist, and other emerging AI development tools. We are looking for a Technical Lead – Java Backend who is passionate about building scalable distributed systems while leveraging AI-assisted development to accelerate engineering productivity without compromising code quality, security, or maintainability. This is a highly hands-on leadership role where you will lead backend development, mentor engineers, establish engineering best practices, and drive AI-enabled software delivery for enterprise-grade applications running on AWS. Your Impact As a Technical Lead, you will: Lead the design and development of scalable backend services. Drive adoption of AI-assisted software engineering across the team. Ensure AI-generated code meets enterprise architecture, security, and quality standards. Mentor engineers in modern Java development and AI-powered workflows. Improve engineering velocity through automation, AI tooling, and best practices. Deliver production-ready software for mission-critical enterprise applications. What You Will Do Backend Technical Leadership Lead development of enterprise-grade backend applications using Java, Spring Boot, and Microservices. Design scalable REST APIs and event-driven architectures. Build secure, highly available distributed systems on AWS. Make architectural decisions balancing scalability, maintainability, and performance. Conduct design reviews and establish coding standards. AI-Assisted Software Development Utilize GitHub Copilot, Claude Code, Cursor AI, Windsurf, Gemini Code Assist , and similar AI development tools to improve engineering productivity. Review and validate AI-generated code to ensure correctness, security, performance, and maintainability. Drive AI-enabled development practices including: Code refactoring Automated debugging Promote responsible use of AI while maintaining human engineering oversight. Software Engineering Excellence Build highly maintainable backend services following SOLID principles and clean architecture. Optimize application performance and scalability. Implement secure authentication and authorization mechanisms. Improve CI/CD pipelines and deployment automation. Participate in production troubleshooting and performance tuning. Mentor developers through code reviews and technical coaching. Work closely with Product Owners, Architects, QA Engineers, and DevOps teams. Translate business requirements into scalable technical solutions. Support Agile/Scrum ceremonies and technical planning. What You Will Bring 10+ years of hands-on Java development experience. Strong expertise in: Spring Boot Spring MVC Spring Security Spring Data JPA Spring Cloud Experience building enterprise-scale Microservices. Distributed Systems REST APIs Event-driven architecture Asynchronous processing Distributed transactions Resiliency patterns API Gateway AWS (ECS/EKS, Lambda, API Gateway, RDS, DynamoDB, S3, IAM, CloudWatch) Docker Terraform/CDK Jenkins/GitHub Actions Databases Oracle SQL Server DynamoDB Redis Query optimization Performance tuning AI-Assisted Development Hands-on experience using one or more of: Cursor AI Windsurf Amazon Q Developer ChatGPT Enterprise (development workflows) Experience with: AI-assisted coding AI code review AI-generated unit testing Prompt engineering for software development Domain-Driven Design (DDD) Design Patterns Test-Driven Development (TDD) Behavior-Driven Development (BDD) Secure coding practices Leadership Experience leading Agile engineering teams. Excellent mentoring and coaching skills. Strong stakeholder communication. Ability to drive technical discussions and engineering decisions. Nice to Have Experience modernizing monolithic applications into Microservices. Experience building AI-native developer workflows. Exposure to Agentic AI systems. Experience with MCP (Model Context Protocol). Knowledge of Retrieval-Augmented Generation (RAG). Experience integrating LLM APIs into enterprise applications. Experience working in BFSI or other regulated industries. Knowledge of observability tools such as Grafana, Prometheus, ELK, Datadog, or Splunk. The InRhythm Consultant At InRhythm, every consultant is expected to demonstrate: Ownership and accountability Continuous learning Collaboration and knowledge sharing Bias toward measurable business outcomes At InRhythm, we believe in building a workplace where engineers thrive. We offer: 401(k) Matching Scalable PTO Weekly Happy Hours & Team Events Opportunity to work with cutting-edge AI-assisted software development practices #J-18808-Ljbffr InRhythm