Polyglot Engineer

We are looking for a modern Full Stack Developer with 3-6 years of experience who can build scalable, secure, cloud-native applications across different technology stacks. This is not a conventional Node.js developer or frontend/backend ticket developer role. We are looking for engineers who are comfortable working as polyglot full stack developers — people who can work across frontend, backend, APIs, databases, cloud-native platforms, and AI-assisted

engineering workflows.Our current ecosystem includes technologies such as TypeScript, Node.js, Angular, LoopBack, cloud-native platforms, SaaS architectures, microservices, and open-source frameworks. However, we are not hiring for one fixed stack only. Depending on project needs, the role may involve working with Python, Go, Java, Rust, TypeScript, Node.js, Angular, or other modern technologies.

In the AI era, coding alone is no longer enough. AI tools can generate code quickly, but good engineers must know what to build, how to design it, how to validate it, how to secure it, how to test it, how to operate it, and how to improve it over time.

We are looking for developers who use AI as a productivity multiplier, but do not blindly rely on AI-generated code. We do not want vibe coders. We want engineers with strong fundamentals, architectural awareness, product thinking, debugging ability, and delivery ownership.

Preferred Location - Noida/Mohali

Key Responsibilities

● Full Stack & Polyglot Engineering:

-Design, develop, test, and maintain full stack applications across frontend, backend, APIs, and databases.

-Work across multiple programming languages and frameworks based on project needs.

-Build backend services, APIs, workers, integrations, and microservices using suitable technologies such as TypeScript, Node.js, Python, Go, Java, Rust, or similar.

-Develop responsive, maintainable frontend applications using Angular or other modern frontend frameworks.

-Build reusable, modular, extensible, and testable components.

-Work with relational and NoSQL databases, including schema design, query optimization, migrations, and data access patterns.

-Contribute to internal accelerators, reusable frameworks, SDKs, engineering libraries, and open-source initiatives where applicable.

● AI-Enabled SDLC & Developer Productivity:

-Use AI tools such as Claude, GitHub Copilot, Codex, ChatGPT, or similar tools to improve engineering productivity.

-Apply AI across the SDLC, including requirement analysis, technical design support, code scaffolding, refactoring, unit test generation, documentation, debugging, and troubleshooting.

-Use AI to accelerate development while maintaining strong ownership of design decisions, code quality, security, testing, and production readiness.

-Critically review and validate AI-generated code for correctness, maintainability, security, performance, licensing risks, and architectural fit.

-Identify areas where AI can improve team productivity, automation, testing, documentation, and operational efficiency.

-Demonstrate responsible AI usage by avoiding blind reliance on generated code and ensuring human accountability for final deliverables.

● Cloud-Native & Architecture Awareness:

-Build applications that are container-ready and suitable for deployment on Kubernetes or cloud-native platforms.

-Understand Docker, Kubernetes basics, environment configuration, secrets, health checks, autoscaling, and deployment patterns.

-Understand microservices concepts such as service boundaries, API contracts, resilience, retries, idempotency, distributed communication, and eventual consistency.

-Apply API design and governance practices, including versioning, backward compatibility, validation, error handling, and documentation.

-Understand multi-tenant SaaS application concepts such as tenant isolation, configuration-driven behavior, extensibility, and scalable service design.

-Collaborate with architects and senior engineers to convert architecture guidelines into working software.

-Participate in technical discussions and contribute practical design inputs.

Quality, Security & Observability:

-Write unit tests, integration tests, and automated test cases.

-Follow secure coding practices aligned with OWASP principles.

-Understand common security concerns such as authentication, authorization, input validation, secrets handling, dependency vulnerabilities, and secure API design.

-Add meaningful logs, metrics, traces, and error handling to support production observability.

-Work with observability tools such as OpenTelemetry, Prometheus, Grafana, Signoz, ELK, Datadog, or similar tools where applicable.

-Support debugging, root-cause analysis, and performance improvement of production and pre-production issues.

-Review code not only for functionality, but also for maintainability, extensibility, security, testability, and operational readiness.

● Collaboration & Ownership:

-Work closely with product owners, architects, QA, DevOps, and other engineers.

-Understand business requirements and translate them into reliable technical implementation.

-Communicate clearly in written and verbal formats.

-Document technical decisions, assumptions, APIs, implementation details, and operational considerations.

-Take ownership of assigned modules from design to development, testing, deployment support, and maintenance.

-Continuously improve personal skills, team practices, and engineering productivity.

Required Skills:

-Strong programming fundamentals in at least one backend language such as TypeScript, JavaScript, Python, Go, Java, Rust, or similar.

-Ability and willingness to work across multiple languages and frameworks.

-Good understanding of full stack development, including frontend, backend, APIs, databases, and integrations. Experience with modern frontend development using Angular, React, Vue, or similar.

-Good understanding of REST APIs, API contracts, validation, error handling, authentication, and authorization flows.

-Experience with SQL databases such as PostgreSQL, MySQL, or similar.

-Understanding of Git, pull requests, branching strategies, and code review workflows.

-Ability to write clean, maintainable, modular, and testable code.

Preferred Technology Exposure:

The following are preferred, but not mandatory:

● TypeScript / JavaScript, Node.js, Angular, LoopBack 4, Express.js, Fastify, NestJS, or similar backend frameworks

● Python, Go, Java, or Rust

● Docker and Kubernetes

● Cloud platforms such as AWS, Azure, or GCP

● CI/CD pipelines

● Open-source frameworks and reusable engineering libraries

AI & Modern Engineering Productivity:

-Hands-on usage of AI-assisted development tools such as Claude, GitHub Copilot, Codex, ChatGPT, or equivalent tools.

-Ability to use AI for productivity while maintaining engineering quality.

-Ability to review, debug, and improve AI-generated code.

-Basic understanding of prompt writing for technical tasks.

-Awareness of risks around AI-generated output, including hallucinations, security flaws, weak design, outdated dependencies, poor test coverage, and licensing concerns.

Cloud-Native Awareness:

-Basic understanding of Docker and containerized application development.

-Exposure to Kubernetes concepts such as pods, services, deployments, config maps, secrets, ingress, and autoscaling.

● Awareness of cloud-native application design principles.

● Understanding of CI/CD and automated deployment workflows.

● Familiarity with observability, monitoring, logging, and distributed tracing concepts.

Architecture & Design Awareness:

-Understanding of software design principles such as SOLID, separation of concerns, dependency injection, modularity, clean layering, and interface-driven design.

-Awareness of microservices patterns and trade-offs.

-Ability to reason about scalability, performance, security, maintainability, and observability.

-Ability to identify tightly coupled, fragile, or hard-to-maintain solutions.

-Ability to select the right tool, framework, or language for the problem rather than forcing every problem into one stack.

Good to Have:

● Experience building SaaS products, multi-tenant platforms, or enterprise-grade applications.

● Experience with microservices and distributed systems.

● Experience with open-source contribution or open-source-based product development.

● Experience in telecom, healthcare, fintech, CRM, or enterprise SaaS domains.

● Experience with message brokers such as Kafka, RabbitMQ, NATS, or similar.

● Experience with OpenTelemetry, Prometheus, Grafana, Signoz, ELK, Datadog, or similar observability tools.

● Exposure to GenAI APIs, RAG systems, semantic search, AI agents, or LLM-based automation.

● Understanding of secure SDLC, dependency vulnerability scanning, SAST/DAST, and supply chain security.

● Experience with contract-first API development, OpenAPI specifications, or automated API documentation.

● Exposure to infrastructure-as-code, Helm, Terraform, or cloud deployment automation.

Education:

● Preferred qualifications:

-B.Tech / B.E. / BCA / MCA / M.Tech or equivalent practical experience.

-Strong hands-on engineering ability demonstrated through professional work, projects, open-source contributions, or practical technical assessments.

Experience

● 3–6 years of relevant software development experience.

● Stronger candidates with slightly lower experience may be considered if they demonstrate strong fundamentals, polyglot adaptability, AI-enabled development maturity, and production-quality engineering mindset.