MERN Developer
Zensar
Full Time6+ yearsPosted 6 days ago
Let the right jobs find you
Get personalised suggestions from verified company career pages, matched to your role, location, level, and skills.
Overview
Position Type
Full Time
Experience
6+ years
Job Description
Role Overview
Design solutions, drive best practices, and mentor development teams. Follow and enforce Agile delivery methodology
Key Responsibilities
- Define system architecture and technical roadmap for MERN-based solutions.
- Design solutions and lead conversations for design approvals.
- Lead development teams and mentor engineers.
- Ensure code quality, security, and performance standards.
- Conduct code reviews and enforce best practices.
- Collaborate with stakeholders on solution design.
- Drive CI/CD, DevOps integration, and release planning.
- Identify risks and propose mitigation strategies.
- Well versed in using AI tools like GitHub Copilot.
Required Skills, Qualifications & Experience
- MERN Stack – expert level (React.js, Node.js, MongoDB, NestJS)
- Angular (good to have for hybrid ecosystems)
- AWS architecture and deployment
- Microservices & API design patterns
- Database expertise (MongoDB, Postgres, Oracle)
- CI/CD pipelines (GitHub Actions, Jenkins)
- JavaScript ES6+ including TypeScript
- Authentication & security (JWT, OAuth, OWASP)
Good to Have
- Angular for hybrid front-end ecosystems.
- GraphQL API design.
- Infrastructure-as-Code (Terraform / AWS CDK).
- Rule engine architecture knowledge (Workflow orchestration BPM, CIB7) – process modelling (BPMN 2.0 / DMN 1.3), Workflow orchestration deployment on AWS, and integrating workflow engines into microservices ecosystems.
What Makes You Stand Out?
- Advanced ability to analyse complex problems and propose viable solutions.
- Strong relationship building and customer focus.
- Ability to manage multiple concurrent initiatives.
- Insurance domain experience.
- Ability to learn and adopt new technologies as per requirement.
AI & GitHub Copilot Capabilities
- Champion GitHub Copilot adoption across the engineering team — define prompting standards and best-practice guidelines.
- Use Copilot Chat and AI models to evaluate architectural trade-offs, generate architecture decision records (ADRs).
- Leverage AI-powered code analysis tools to produce technical debt heat maps and guide sprint refactoring priorities.
- Automate PR review summaries using Copilot, freeing senior engineers to focus on high-value feedback.
- Integrate AI-assisted security scanning (GitHub Advanced Security, Copilot Autofix) into CI/CD gates.
- Use AI tools to generate Infrastructure-as-Code (Terraform / CDK) from architecture diagrams.
- Explore LLM-powered search over internal codebases for onboarding and knowledge transfer acceleration.