Senior Software Engineer

Required Skills & Qualifications

4–6 years of hands-on experience in software development with React.js (Front-End) and Java (Back-End).

Strong expertise in Java, Spring Boot, and RESTful API development with a solid understanding of design patterns and object-oriented programming principles.

Experience in designing and developing scalable microservices and distributed systems.

Strong understanding of Artificial Intelligence and Machine Learning concepts, including Large Language Models (LLMs), AI Agents, Prompt Engineering, Retrieval-Augmented Generation (RAG), and AI-powered application development.

Hands-on experience integrating AI services and frameworks such as OpenAI APIs, Azure OpenAI, LangChain, Semantic Kernel, or similar technologies.

Experience leveraging AI-assisted development tools such as GitHub Copilot, Microsoft Copilot, ChatGPT, or equivalent to improve development productivity and software quality.

Strong Java and React.js programming skills, including architecture, prototyping, development, testing, performance tuning, profiling, and troubleshooting.

Hands-on experience with messaging and event-driven architectures using Apache Kafka.

Familiarity with in-memory caching technologies such as Redis and Memcached.

Strong understanding of relational databases, preferably Oracle, including database design, query optimization, indexing, and performance tuning.

Experience with NoSQL databases, preferably Cassandra.

Hands-on experience with Docker, Kubernetes, Jenkins, and CI/CD pipelines.

Good understanding of cloud-native application development and deployment practices.

Strong analytical, debugging, and problem-solving skills with the ability to troubleshoot complex production issues.

Excellent communication and collaboration skills with the ability to work effectively in cross-functional teams.

Key Responsibilities

Design, develop, and maintain scalable full-stack applications using React.js and Java/Spring Boot.

Architect and implement robust REST APIs and microservices for high-performance distributed systems.

Develop and support event-driven architectures leveraging Kafka and related technologies.

Deploy, monitor, and troubleshoot applications running in Kubernetes-based environments.

Collaborate with product management, engineering, and platform teams to deliver high-quality solutions.

Drive technical design discussions and contribute to architectural decisions.

Integrate AI-powered capabilities into products and workflows, including LLM-based and agentic solutions.

Evaluate and adopt emerging AI technologies to enhance product functionality and engineering efficiency.

Utilize AI-assisted development tools to improve code quality, testing coverage, documentation, and developer productivity.

Participate in code reviews, mentor junior engineers, and promote engineering best practices.

Ensure application performance, reliability, scalability, and security through proactive engineering practices.