Description

Must-Have Technologies: ReactJS, Python, Java 17+, Microservices, AWS/Azure, RDBMS, NoSQL

Required Skills
10+ years of hands-on software development experience, with deep expertise in modern Java full-stack development.
Strong command of Java frameworks and libraries, including Spring, Spring Boot, and
Hibernate.
Proven experience building single-page web applications using ReactJS, Bootstrap, and Node.js.
Strong hands-on proficiency with Python for scripting, automation, data processing, and backend services.
Proven ability to build responsive, intuitive user interfaces and translate UI/UX mockups into production-ready experiences.
Demonstrated experience architecting and implementing microservices and event-driven systems using messaging platforms such as Kafka or RabbitMQ.
Expertise developing and maintaining RESTful APIs, backend services, and database schemas across relational (SQL Server, PostgreSQL) and NoSQL (MongoDB, Elasticsearch) platforms.
Strong SQL development skills, including query optimization and performance tuning.
Hands-on experience deploying and operating containerized microservices on AWS and/or Azure, applying cloud-native patterns and infrastructure-as-code.
Working knowledge of modern security frameworks and standards such as OAuth 2.0,
OpenID Connect, and JWT.
Proven ability to proactively detect and remediate security vulnerabilities across application code and infrastructure, ensuring compliance within established SLAs.
Experience with modern testing frameworks (Jest, Mocha, Chai) and a commitment to test- driven development, including unit and integration testing.
Ability to enforce engineering best practices through peer code reviews, architectural
standards, and raising the bar on code quality.
Proven ability to troubleshoot complex, cross-stack production issues and drive root-cause analysis to resolution.
Experience participating in Agile ceremonies and managing work and releases through Jira and Azure DevOps.
Hands-on experience with Agile methodologies and DevOps culture across the software delivery lifecycle.


AI & Generative AI
Practical experience integrating Large Language Models into applications via APIs (e.g.,OpenAI, Anthropic Claude, Azure OpenAI, AWS Bedrock).
Familiarity with prompt engineering, Retrieval-Augmented Generation (RAG), embeddings, and vector databases.
Experience integrating AI capabilities — LLMs, embeddings, RAG pipelines, agentic
workflows — into existing applications and new product features.
Experience collaborating with data science and ML teams to operationalize models, build evaluation pipelines, and deploy production-ready AI services

Key Skills

Education

Any Graduate