Full - Stack Engineer

TA Digital; Chennai District; On-site; INR 1,500,000 - 2,100,000; Full time

Job summary

TA Digital in India is seeking a skilled software engineer to build and integrate AI-enabled applications across frontend and backend. You will implement interfaces for AI agents, connect AI systems to operational platforms, and drive robust, scalable data pipelines.

You will design REST/GraphQL APIs, adopt microservices, and apply AWS services with CI/CD and observability practices to ensure reliability and security of deployments.

Qualifications

• Strong experience with modern web frameworks (React) and backend development (Python).
• Proficiency in API development (REST, GraphQL) and microservices architectures.
• Knowledge of AWS services (Lambda, ECS, API Gateway, CloudFormation, CDK).
• Experience with DevOps tools and CI/CD pipelines (Bonus).
• Familiarity with AI/ML application integration patterns.
• Database(MS SQL, postgres, cloud DB, etc. ).
• Some proficiency in Gen AI and AI tools is a plus.
• Software development experience designing and building full-stack applications, with hands‑on work across frontend (e.g., React, Next.js, Angular, Vue) and backend (APIs, microservices, data layers).
• Hands‑on development with modern programming languages (Python preferred, FastAPI, TypeScript, JavaScript, Kotlin).
• Cloud architecture and solution implementation experience on AWS or comparable cloud platforms.
• Experience with Infrastructure as Code (Terraform, AWS CDK, CloudFormation), CI/CD pipelines and DevOps practices.
• Background in asynchronous API design and implementation (REST, GraphQL, gRPC) and identity protocols (OpenID Connect, OAuth 2.0).
• Experience with distributed systems, event‑driven architectures, and microservices patterns at scale.
• Familiarity with observability and monitoring practices (OpenTelemetry, CloudWatch, Datadog, AppInsight, Loganalytics) with a focus on operational excellence.
• Unit testing framework - pytest, NUnit. Integration testing end‑to‑end. (backend testing).
• Application security framework (Blackbox).
• RBAC: JWT token, Entra ID, Active Directory.
• DB optimisation, session management.
• Experience building applications that integrate generative AI or large language model capabilities (RAG, chat interfaces, agent workflows, LLM‑powered features).
• Experience using AI‑assisted development tools (GitHub Copilot).
• Experience with AI agent architectures, orchestration patterns, and emerging protocols (MCP, A2A).
• Agentic software development methodologies using AI agents to accelerate development workflows.

Responsibilities

• Build and develop technical work outputs for each work package.
• Implement user interfaces and integration layers for AI agents.
• Develop APIs and data pipelines connecting AI systems to operational platforms.
• Build monitoring and observability solutions for AI applications.
• Implement DevOps automation and CI/CD pipelines.
• Support SDLC automation initiatives and tooling integration.

Skills

React

Python

REST API

GraphQL

Microservices

AWS

CI/CD

AI/ML integration

SQL databases

Next.js

TypeScript/JavaScript

Kubernetes

Terraform

AWS CDK

CloudFormation

OpenTelemetry

Datadog

gRPC

JWT

OpenID Connect/OAuth 2.0

pytest

NUnit

Blackbox security

AI agents

GitHub Copilot

Tools

Terraform

AWS CDK

CloudFormation

OpenTelemetry

Datadog

Next.js

Angular

Vue

PostgreSQL

MS SQL

Cloud DB

OpenID Connect

OAuth 2.0

Job description

Responsibilities:

• Build and develop technical work outputs for each work package.


• Implement user interfaces and integration layers for AI agents.


• Develop APIs and data pipelines connecting AI systems to operational platforms.


• Build monitoring and observability solutions for AI applications.


• Implement DevOps automation and CI/CD pipelines.


• Support SDLC automation initiatives and tooling integration.

Requirements:

• Strong experience with modern web frameworks (React) and backend development (Python).


• Proficiency in API development (REST, GraphQL) and microservices architectures.


• Knowledge of AWS services (Lambda, ECS, API Gateway, CloudFormation, CDK).


• Experience with DevOps tools and CI/CD pipelines (Bonus).


• Familiarity with AI/ML application integration patterns.


• Database(MS SQL, postgres, cloud DB, etc. ).


• Some proficiency in Gen AI and AI tools is a plus.


• Software development experience designing and building full-stack applications, with hands‑on work across frontend (e. g., React, Next.js, Angular, Vue) and backend (e. g., APIs, microservices, data layers).


• Hands‑on development with modern programming languages (e. g., Python preferred, FastAPI, TypeScript, JavaScript, Kotlin ).


• Cloud architecture and solution implementation experience on AWS or comparable cloud platforms.


• Experience with Infrastructure as Code (e. g., Terraform preferred, AWS CDK, CloudFormation), CI/CD pipelines and DevOps practices.


• Background in asynchronous API design and implementation (REST, GraphQL, gRPC) and identity protocols (OpenID Connect, OAuth 2.0).


• Experience with distributed systems, event‑driven architectures, and microservices patterns at scale.


• Familiarity with observability and monitoring practices (e. g., OpenTelemetry, CloudWatch, Datadog, AppInsight, Loganalytics) with a focus on operational excellence.


• Unit testing framework - e. g pytest, NUnit. Integration testing end‑to‑end. (backend testing).


• Application security framework (e. g., Blackbox).


• Role‑based authentication and authorisation: JWT token, Entra ID, Active Directory.


• DB optimisation, session management.


• Experience building applications that integrate generative AI or large language model capabilities (e. g., RAG, chat interfaces, agent workflows, LLM‑powered features).


• Experience using AI‑assisted development tools as part of the software development workflow (e. g., GitHub Copilot).


• Experience with AI agent architectures, orchestration patterns, and emerging protocols (e. g., MCP, A2A), with hands‑on experience building multi‑agent systems.


• Experience with agentic software development methodologies using AI agents to accelerate development workflows, including coding, testing, debugging, and code review.