Tech architect (node+golang+react)

Job Description :

We’re looking for a Technical Architect – Full Stack with 8+ years of experience in building, architecting, and delivering scalable, high-performance web applications. The role requires deep expertise in Node.js, React.js, Go (Golang), and Graph QL, along with strong experience in system architecture, database design, and cloud-native deployments. The Ideal Candidate will lead technical strategy, ensure system reliability, and drive engineering excellence across teams.

Role & Responsibilities :

Architect and build scalable applications using

Node.js ,

Golang , and

React.js

Develop and maintain

high-performance APIs and microservices

with

Graph QL

and

Apollo.

Create

modern, reusable frontend components

with

React.js

and

Type Script.

Design and optimize

Postgre SQL(or any other Sql)

databases

Implement

CI / CD pipelines ,

Terraform , and

Kubernetes

deployments on

AWS / GCP.

Ensure reliability through

automated testing

using

Jest ,

Cypress , and

Testing Library.

Collaborate across teams on

architecture ,

performance optimization , and

best practices.

Skills Required : 8+ years

of hands-on experience in

full-stack engineering ,

architecture , and

system design.

Expert proficiency in

Node.js

for scalable backend architecture.

Deep experience with

React.js

and modern frontend development.

Strong command of

Go (Golang)

for performant, distributed systems.

In-depth knowledge of

Graph QL

and

Apollo Client / Server

for scalable APIs.

Extensive experience with

Postgre SQL

(or any other Sql) databases.

Advanced

Type Script / Java Script

expertise across the full stack.

Strong focus on

testing and code quality

using

Jest ,

Cypress , and

Testing Library.

Solid understanding of design

principles

and

C4 modelling.

Good to have Skills :

Experience in building and maintaining scalable, maintainable solutions using

React ,

React Native , and

Express.js

(or similar frameworks).

Experience with

Kafka

for event-driven systems.

Knowledge of

Temporal

for workflow orchestration.

Proficiency with

Docker

and

Kubernetes

for containerized deployments.

Working knowledge of

Redis

for caching and session management.

Experience with

Data Dog

or similar monitoring tools.

Experience with AI frameworks like

Lang Chain ,

Lang Graph , and

RAG pipelines.

Exposure to

Open AI API

for LLM-based application development.