Job Description
We are looking for a dynamic and motivated Software Engineer to join our team and contribute to building next-generation cloud-native, API-first, microservices-driven platforms. This role is ideal for someone passionate about full-stack development and eager to learn and grow their skills in a fast-paced Agile environment leading the ‘learn by doing’ principle. You will work alongside experienced engineers and systems experts to develop scalable, secure, and intelligent CPQ (Configure, Price, Quote) solutions that support our sales and pre-sales channels. The ideal candidate thrives at the intersection of complex distributed systems, cutting-edge frameworks, and enterprise-grade architectures, bringing both technical depth and creative innovation to deliver world-class digital experiences. In our fast-paced, Agile-first environment, you won’t just build software—you’ll define the future of intelligent platforms.
Why This Role Matters:
This role offers an exciting opportunity to contribute to a strategic transformation initiative for CPQ Transformation. As a Software Engineer, you will support the innovation and development of next-generation telco CPQ solutions that redefine how products are conceived, configured, quoted, and sold. By applying your growing technical skills and problem-solving mindset, you will help build modern, intelligent, light weight, intuitive and user-friendly platforms that aim to set new standards in performance and usability. Every task you undertake will contribute to accelerating revenue growth, enhancing customer satisfaction, and supporting a sustainable competitive advantage. This is your chance to not only develop software but also to be part of reshaping the future of the telecom industry.
Job Description
To assist in the design, development, and deployment of next-generation cloud-native platforms that are AI/ML-powered, API-first, and microservices-driven, helping the organization deliver innovative digital solutions. In this role, you will support the transformation of legacy systems into modern, intelligent ecosystems by contributing to the integration of advanced machine learning models into production-ready platforms. You will be part of a team that fosters technical excellence, agility, and continuous innovation. The mission is to help accelerate business growth, improve operational efficiency, and enhance competitive advantage by building scalable, secure, and future-ready systems that push the boundaries of what’s possible.
Activities and Responsibilities:
- Assist in the development and refactoring of Telco CPQ systems using one or more backend frameworks such as .NET 8+, C# 12, ASP.NET Core MVC, Web API, Entity Framework Core, and LINQ, JAVA Springboot, Quarkus to improve code quality and maintainability.
- Support front-end development using one or more frameworks such as Blazor, React, Angular, and Vue/Nuxt.js to create modular and user-friendly interfaces.
- Collaborate with senior developers to implement microservices and API-first designs using recommended design patterns and architectural strategy.
- Participate in cloud-native deployments using Docker and Kubernetes under guidance.
- Collaborate with senior engineers to integrate AI/ML components and embed machine learning models into CPQ workflows, enhancing platform intelligence.
- Contribute to writing automated tests using frameworks like Playwright and Robot Framework to ensure zero touch software quality assurance.
- Assist in developing Python-based APIs using FastAPI framework for AI/ML services.
- Support creation and maintenance of DevOps pipelines for continuous integration and delivery.
- Identify opportunities for automation and adoption of generative AI technologies to enhance business processes.
- Work with various databases including MongoDB, MySQL, GraphDB, VectorDB and PostgreSQL to support application data needs.
- Assist in building and maintaining data pipelines to support real-time analytics and AI workloads.
- Learn and apply best practices in system design to build performant, scalable, resilient, secure, and highly available systems.
- Navigate ambiguity and complexity to propose smart, practical solutions for complex business challenges.
- Understand and ensure technology and tooling adoption aligns with existing enterprise architecture (EA) guardrails.
- Work closely with cross-functional teams to understand requirements and deliver solutions aligned with business goals.
- Continuously improve coding skills and technical knowledge through mentorship and training.
Key Skills, Knowledge and Abilities
Programming Languages & Frameworks:
- .NET 8+, C# 12, ASP.NET Core MVC, Web API, Entity Framework Core, LINQ
- Front-end: Blazor, React, Angular, Vue.js / Nuxt.js
- Python with FastAPI framework
- Microservices architecture, API-first design (REST, gRPC)
Databases:
- MongoDB, MySQL, PostgreSQL, GraphDB, VectorDB etc – basically can work on both NoSQL and relational databases
Cloud & DevOps:
- Cloud-native technologies with Azure, AWS, GCP
- Containerization with Docker and orchestration using Kubernetes
- CI/CD pipeline creation and maintenance using Azure DevOps, GitHub Actions
AI/ML & Deep Learning:
- Basic understanding of AI, Machine Learning, and Deep Learning concepts
- Familiarity with common ML algorithms such as Linear Regression, Random Forest,XGBoost etc.
- Exposure to integrating AI/ML models and Large Language Models (GPTx, Claudex,Geminix)
- Ability to work with code assist tools like GitHub CoPilot, KiloCode
- Understanding of prompt engineering, LLM proxies, MCP Servers, and agentic workflows
Testing & Automation:
- Basic Experience or exposure to automation testing frameworks such as Playwright and Robot Framework
- Understanding of Test-Driven Development (TDD) and Behaviour-Driven Development (BDD) principles
Design Patterns & Software Architecture Principles:
- Knowledge of common design patterns and various data structure algorithms
- Understanding of various microservices architecture patterns
- Basic understanding of designing scalable, resilient, secure, and highly available systems
- Awareness of enterprise architecture guardrails and ensuring technology adoption compliance
Personal Attributes
- Demonstrates strong analytical and problem-solving abilities with a proactive approach to overcoming challenges in fast-paced, Agile environments.
- Excellent interpersonal and communication skills, enabling effective collaboration with cross-functional teams and stakeholders at all levels.
- Proven ability to manage multiple priorities efficiently, ensuring timely delivery of high-quality work under pressure.
- Highly motivated and passionate about driving digital transformation initiatives and contributing innovative solutions that add tangible business value.
Eligibility Criteria
- Bachelor’s/master’s degree in computer science, Engineering, or related field.
- 0-2 years of experience in software development or internships/projects demonstrating full-stack development skills
- Basic hands-on experience or academic projects involving one or more in full stack tech across .NET Core, C#, Python with Fast API framework, as well as one or more of the following front-end frameworks such as Angular, React, Vue.js etc
- Familiarity with cloud-native concepts and containerization is a plus
- Passion for AI/ML and interest in integrating intelligent features into software solutions
- Excellent communication, negotiation, and stakeholder management skills to bridge technical depth with business outcomes.
- Proven ability to design cost-effective, scalable AI-driven engineering solutions that balance innovation with operational efficiency.
Good to Have:
- Basic knowledge and understanding of various Agile Wow-Scrum, XP, Kanban, SAFE etc
- Basic understanding or familiarity with collaboration and delivery tools like Jira, Confluence, Azure DevOps, GitHub Actions.
- Basic understanding of data engineering /pipeline tools (Spark, Kafka, Airflow) and cloud-native data platforms for enterprise grade ML workloads.
- Understanding of ethical AI practices-responsible AI, bias mitigation, and responsible AI deployment in enterprise contexts.
