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)