Kaleris off campus drive for Associate Software Engineer freshers with 0-2 years exp apply Full Time NEW

Kaleris is seeking a Software Engineer join our talented team in building the next generation of our products at Kaleris. In this position you will have an opportunity to make major contributions to our next generation transportation and logistics software products and application features. You’ll collaborate closely with colleagues to outline project requisites and build state-of-the-art software and applications. Demonstrating a rapid learning ability and possessing strong communication skills is essential.

Responsibilities 

• Assist in analyzing requirements, designing solutions, developing code, writing unit tests, and delivering quality custom software enhancements.
• Develop and maintain secure, scalable, and reliable application components under the guidance of senior engineers.
• Support the creation of RESTful services, integrations, backend logic, data access components, and configuration changes for field development projects.
• Collaborate with product management, quality assurance, project managers, and senior developers to clarify requirements and deliver well-tested functionality.
• Use AI-assisted development tools, such as GitHub Copilot or similar coding assistants, to support code generation, refactoring, documentation, test creation, and troubleshooting while validating all outputs before use.
• Create clear prompts and provide structured context to AI tools to improve development efficiency, while following company policies for data security, confidentiality, and responsible AI usage.
• Review AI-generated code for correctness, maintainability, security, licensing concerns, and alignment with Navis engineering standards.
• Participate in code reviews, feature reviews, and technical discussions by incorporating feedback and learning from more experienced team members.
• Write and maintain technical documentation, including solution notes, implementation details, use cases, test cases, and support handover information.
• Troubleshoot defects and production issues with support from senior engineers, using logs, debugging tools, test data, and AI-assisted analysis where appropriate.
• Participate in development activities, including estimation, delivery planning, daily stand-ups, demos, and retrospectives.
• Continuously build knowledge of N4, enterprise Java development, integrations, cloud concepts, databases, messaging technologies, and secure coding practices.

Requirements 

• BE/BTech/MCA/MSC IT, Bachelor’s degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience.
• 0–2 years of software engineering experience; internships, academic projects, bootcamp projects, or relevant personal projects may be considered.
• Foundational knowledge of object-oriented programming, application design, data structures, and common design patterns.
• Hands-on experience or strong academic exposure to Java application development.
• Exposure to RESTful application development using Spring, Spring Boot, or similar frameworks.
• Basic understanding of software development lifecycle practices, version control, unit testing, integration testing, and debugging.
• Familiarity with JUnit or similar test frameworks.
• Basic understanding of secure coding, application performance, scalability, reliability, and maintainability principles.
• Exposure to relational databases and SQL; familiarity with NoSQL databases such as Cassandra is an advantage.
• Exposure to messaging technologies such as Kafka or JMS is an advantage.
• Ability to work in a fast-paced, collaborative, test-driven, and iterative development environment; Agile experience is a plus.
• Strong willingness to learn, accept feedback, solve problems, and contribute positively to team delivery.
• Good written and spoken English communication skills.

AI Skills & Responsibilities

• Practical understanding of how to use AI coding assistants responsibly for coding, debugging, documentation, and test generation.
• Ability to write clear prompts, validate AI-generated outputs, and refine prompts based on technical feedback or failed tests.
• Awareness of AI limitations, including hallucinated code, insecure suggestions, outdated library usage, and incorrect assumptions.
• Ability to protect confidential customer, company, and source-code information when using AI-enabled tools.
• Interest in applying AI to improve engineering workflows, such as generating unit tests, summarizing logs, drafting technical documentation, identifying repetitive development tasks, and improving developer productivity.
• Willingness to learn emerging AI engineering practices, including prompt patterns, code review of AI outputs, AI-assisted test coverage, and responsible automation.

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