Software Engineering Professional

About the role

We are looking for a Software Engineering Professional to contribute to the adoption of AI-assisted Software Development Lifecycle (SDLC) practices across engineering teams.

In this role, you will work across the software engineering lifecycle — from understanding requirements and designing solutions to development, testing, deployment, and production support — using modern engineering practices and AI-powered tools to improve productivity, quality, and delivery speed.

You will work closely with senior engineers, architects, product teams, and other stakeholders to build secure, scalable, resilient, and maintainable applications.

What you’ll be doing

AI-Assisted Engineering

• Use AI-powered tools to accelerate software development activities such as:
• Code generation and refactoring
• Test case generation
• Technical documentation
• Code analysis and troubleshooting
• Design and development acceleration
• Experiment with AI-assisted development approaches and rapidly build POCs and prototypes to validate technical and business requirements.
• Apply spec-driven development practices to improve consistency and quality across the development lifecycle.
• Explore and contribute to solutions using modern AI engineering approaches such as RAG, MCP, and automation tools.

Software Design & Development

• Contribute to the design and development of API-first and microservices-based applications.
• Develop and maintain high-quality backend APIs and frontend applications using technologies such as: Java / Spring Boot, Node.js, Python, React / Angular    
• Follow OpenAPI specifications, enterprise development standards, and established architectural guidelines.
• Work with senior engineers and architects to translate requirements into appropriate technical designs.
• Integrate applications with existing enterprise platforms, services, and databases.

Quality Engineering

• Develop automated tests covering: Unit testing, API testing, Integration testing, Functional testing   
• Use AI-assisted approaches to improve test coverage and identify potential defects.
• Apply secure coding practices and contribute to addressing security vulnerabilities.
• Consider performance, scalability, reliability, and maintainability as part of development activities.

Cloud, DevOps & SRE

• Develop and deploy applications using cloud-based environments, preferably AWS.
• Contribute to CI/CD pipeline development and automation.
• Work with DevOps teams to improve build, deployment, and release processes.
• Contribute to application monitoring, logging, alerting, and observability.
• Support investigation and resolution of production issues and contribute to root-cause analysis.
• Help implement improvements to application resilience, performance, and recoverability.

Collaboration & Delivery

• Work closely with product managers, business teams, architects, senior engineers, and operations teams to understand requirements and deliver solutions.
• Participate in Agile ceremonies including refinement, planning, reviews, and retrospectives.
• Communicate technical challenges, risks, dependencies, and progress effectively.
• Contribute ideas for improving engineering practices, automation, quality, and developer productivity.
• Continuously learn and adopt new engineering and AI-assisted development practices.

Essential Skills / Experience

Technical Skills

• Good hands-on experience in software development using one or more of: Java / Spring Boot, Node.js, Python 
• Experience with at least one modern frontend framework, such as:  React, Angular or similar
• Understanding of REST APIs and API-first development.
• Working knowledge of microservices architecture and distributed application concepts.
• Experience working with PostgreSQL, Oracle, or another relational database.
• Basic to good understanding of AWS or another cloud platform.
• Experience with Git, CI/CD, and DevOps practices.

AI & Modern Engineering

• Hands-on exposure to AI-assisted coding and software development tools.
• Understanding of how AI can be used for: Code generation, Code review, Test generation, Documentation, Debugging, Technical design.
• Awareness of modern AI engineering concepts such as: RAG, MCP, AI agents, Prompt/spec-driven development, Developer automation
• Interest in exploring and applying AI to improve software engineering productivity and quality.

Engineering Practices

• Understanding of OpenAPI specifications and RESTful API design.
• Good understanding of software engineering fundamentals including: SOLID principles, Design patterns, Exception handling, Logging, Security, Performance & Scalability
• Understanding of automated testing and test-driven/quality-focused development practices.
• Experience working in Agile/Scrum environments.
• Telecom/domain experience would be an advantage but is not essential.

Soft Skills

• Strong analytical and problem-solving skills.
• Good communication and collaboration skills.
• Ability to work effectively with senior engineers, architects, product teams, and other stakeholders.
• Comfortable working in a fast-changing technology environment.
• Willingness to learn new technologies and experiment with emerging AI and software engineering tools.
• Ability to take ownership of assigned technical tasks while seeking guidance when required.