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 Impact • 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), Generative AI (GenAI)