Senior Java Software Engineer

We are looking for a Senior Software Engineer who will be driving architectural direction, multi-team initiatives, and the development of highly scalable distributed systems. You will partner with Product, Architecture, DevOps and cross-functional engineering teams to deliver impactful technology solutions across a complex digital ecosystem. You will independently define and deliver large-scale, multi-phase projects, mentor engineers, and shape technical strategy. The role also includes leveraging LLMs and GenAI-driven tools to enhance engineering productivity, reduce cycle time, and build the next generation of internal developer experience tools. Technical Leadership

• Drive technical strategy and architecture for complex distributed systems and core platform components.
• Own end-to-end delivery of high-impact, multi-team engineering initiatives.
• Translate ambiguous business requirements into clear, pragmatic technical solutions. Public
• Define technical roadmaps, sequence projects into phases, and ensure timely execution across teams. Software Engineering & System Design
• Architect, develop, and optimize microservices using Java, Spring Boot, Spring Cloud.
• Design scalable, resilient, secure cloud-native applications using Azure/AWS.
• Lead system design reviews, architecture discussions, and technical deep dives.
• Solve complex cross-system issues through deep debugging, performance tuning, and root cause analysis.
• Build frameworks and shared libraries to accelerate development across squads. AI & Engineering Productivity
• Champion adoption of AI-assisted development practices and LLM/GenAI tools across engineering teams to enhance workflows, improve cycle time, and automate routine tasks.
• Define clear guidelines, training, and standards for effective and secure use of AI tools, including prompt engineering, code generation, and review expectations.
• Integrate AI-driven capabilities such as code generation, unit test creation, log analysis, documentation summarization, and code review assistance into the development workflow.
• Establish and enforce engineering best practices for AI-generated code, including human-in-the-loop reviews, coding standards, test automation, secure coding, and design-first development.
• Measure and optimize engineering productivity using AI-related metrics (cycle time, PR throughput, AI-code adoption, defect escape rate, developer satisfaction) and continuously identify opportunities to reduce bottlenecks with AI. Collaboration & Cross-Functional Impac t
• Work closely with Product Owners, Architects, QE, DevOps, and peer engineering teams.
• Communicate technical trade-offs, risks, and decisions clearly to non-technical stakeholders.
• Coordinate across teams to resolve dependencies and align on architectural standards.
• Influence technical direction beyond your immediate team. Team Leadership & Mentoring
• Mentor engineers across multiple teams, guiding them in design, coding, debugging, and best practices.
• Participate actively in hiring and talent development.
• Raise the engineering bar through code reviews, design critiques, and technical leadership.
• Help define and uphold engineering best practices, coding standards, and architectural principles. Ownership & Operational Excellence
• Take full ownership of systems from development to deployment, monitoring, and maintenance.
• Ensure engineering deliverables meet performance, reliability, and security criteria.
• Proactively identify areas for improvement and propose scalable, maintainable solutions.
• Lead incident response, post-mortems, and continuous improvement initiatives. Main Skills Experience applying LLMs/GenAI to improve engineering productivity and developer workflows.
• Prompt engineering experience and familiarity with integrating models into applications.
• Experience with Domain-Driven Design, event-driven systems, CQRS, or enterprise integration patterns.
• Familiarity with Linux systems and container-based deployment architectures.
• Experience with application servers such as Tomcat.
• Contributions to internal platforms or open-source projects.
• Strong leadership qualities with the ability to influence without authority.
• High levels of self-motivation, ownership, and drive.
• Critical thinking abilities and a strong problem-solving mindset.
• Excellent team collaboration skills and a positive, proactive attitude. Deep expertise in Java, J2EE, Spring, Spring Boot, Spring Cloud, and building microservices-based architectures. Hands-on experience with Docker, Kubernetes / OpenShift, and CI/CD pipelines.
• Strong knowledge of working with databases: Oracle, MySQL, MongoDB, Cassandra, etc.
• Experience designing and scaling systems on Azure, AWS, or Google Cloud.
• Excellent problem-solving skills, debugging capabilities, and system-level thinking. Skills:- Java, Spring Boot, Spring Cloud, Microservices, Kafka, Prompt engineering, Caching, GenAI Integration, Apache Kafka, Large Language Models (LLM) and Generative AI (GenAI)