Key Responsibilities

Technical Leadership

- Lead, mentor, and inspire a high-performing engineering team delivering enterprise-grade products.

- Drive architecture, design, development, testing, deployment, and maintenance of scalable business applications.

- Design and implement low-latency, highly available, and high-performance RESTful APIs using Java and Spring Boot.

- Ensure development of reusable, maintainable, secure, and testable code following industry’s best practices.

- Conduct architecture reviews, design discussions, code reviews, and technical mentoring sessions.

- Own technical documentation including HLDs, LLDs, API specifications, and solution design documents.

- Troubleshoot complex production issues and drive root cause analysis and permanent fixes.

- Collaborate with Product Management, QA, DevOps, Product Engineering, and other cross-functional teams to deliver high-quality product releases.

AI-Driven Engineering Responsibilities

- Leverage AI-powered software engineering tools (such as GitHub Copilot, Claude, ChatGPT, Cursor or equivalent) to accelerate software development across the SDLC.

- Utilize AI for requirement analysis, solution design, code generation, unit test generation, documentation, debugging, refactoring, and code optimization.

- Identify opportunities to automate repetitive engineering activities using AI-assisted development practices.

- Establish AI-assisted coding standards while ensuring security, maintainability, and code quality.

- Mentor team members on effective adoption of AI engineering tools and best practices.

- Evaluate AI-generated code for correctness, scalability, security,



and compliance with engineering standards.

- Drive continuous productivity improvements through responsible AI adoption.

Expected Business Outcomes The successful candidate is expected to contribute towards measurable engineering improvements including:

- 20–30% improvement in engineering productivity through effective AI adoption.

- Reduction in development effort across SDLC phases including design, coding, testing, and documentation.

- Faster feature delivery and reduced release cycle time.

- Lower engineering costs through improved developer efficiency.

- Improved code quality through AI-assisted reviews and automated testing.

- Higher unit test coverage and reduced production defects.

- Increased automation across development and deployment processes.

Technical Skills

Mandatory

- Strong proficiency in Java (Java 11/17+)

- Spring Boot

- Spring Framework

- Microservices Architecture

- REST API Development

- Kafka

- RDBMS (Oracle/PostgreSQL/MySQL)

- Multithreading & Concurrency

- Design Patterns

- Distributed Systems

- API Security (OAuth2/JWT)

- Unit Testing (JUnit/Mockito)

- CI/CD (Jenkins/GitLab)

- SonarQube

- Git

Valuable to Have

- Kubernetes

- Docker

- Cloud Platforms (AWS/Azure/GCP)

- Redis

- Elasticsearch

- Prometheus/Grafana





AI & Developer Productivity Skills

Candidates should demonstrate hands-on experience using AI-assisted software engineering tools for improving engineering efficiency.

Preferred Exposure Includes

- GitHub Copilot

- Claude

- ChatGPT

- Cursor AI

- Amazon Q Developer

- IntelliJ AI Assistant

- AI-powered code review tools

- AI-assisted documentation generation

- AI-assisted unit test generation

- AI-assisted debugging and performance optimization

The Candidate Should Understand

- Prompt engineering for software development

- Responsible AI usage

- AI-assisted code validation

- Secure AI-assisted development practices

- AI-driven SDLC optimization

Leadership Skills

- Proven experience leading engineering teams of 5–6 developers.

- Strong analytical and technical implementation decision-making capabilities.

- Experience driving engineering best practices and continuous improvement initiatives.

Engineering Excellence Expectations

- Maintain high code quality standards.

- Improve code coverage through automated testing.

- Drive technical debt reduction initiatives.

- Promote DevSecOps and CI/CD best practices.

- Ensure adherence to secure coding guidelines.

- Champion AI-enabled engineering transformation across the team.

Preferred Experience

- 6–9 years of enterprise software product development experience.

- Experience working in Agile/Scrum environments.

- Exposure to Telecom, FinTech, Digital Payments, or large-scale enterprise products is preferred.

- Experience leading end-to-end product development from design through production support.

📌 Senior Technical Lead (Gurugram)
🏢 Comviva
📍 Gurugram