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GenAI Full Stack Engineer / Fullstack AI Engineer

GenAI Full Stack Engineer / Fullstack AI Engineer

Celebal
  • Posted 8 hours ago
  • Be among the first 10 applicants

Job Description

Role Title: GenAI Full Stack Engineer / Fullstack AI Engineer / Agentic AI Engineer /

GenAI Engineer / AI Engineer – Agentic AI

Experience: 4–8 years

Engagement Type: Full-time

Locations: Noida, Gurgaon, Jaipur, Ahmedabad, Pune, Bengaluru, Hyderabad

Technology Stack: Backend: Python + FastAPI · Frontend: Next.js / React · Cloud & DevOps: AWS ECS/EC2, Docker, CI/CD, Agentic AI / Gen AI, A2A, AGUI, DeepEval, LangFuse, LLM Observability, AWS bedrock agentcore, LangGraph

Role Summary

We are seeking an experienced Full Stack Developer who can own applications end to end — building high-performance Python/FastAPI backends, developing modern Next.js/React front ends, and taking services all the way to production on AWS through containerised, automated CI/CD pipelines. The ideal candidate is comfortable across the entire stack, from data modelling and API design to responsive UI development and cloud deployment, and thrives in a fast-paced, quality-focused delivery environment.

Key Responsibilities

• Design, develop, and maintain full-stack features spanning the Next.js front end and Python/FastAPI backend.

• Build robust, well-documented RESTful APIs with FastAPI, including authentication, validation, and error handling.

• Develop responsive, accessible, high-performance UIs in Next.js/React (SSR/SSG, App Router, state management).

• Build multi-step agent workflows involving tool/function calling, routing, state management, retries, and human-in-the-loop interactions.

• Integrate LLM providers such as OpenAI, Anthropic, AWS Bedrock, or equivalent platforms.

• Implement RAG pipelines for enterprise knowledge retrieval using vector databases/search platforms such as OpenSearch, or similar technologies.

• Model data and design database schemas; write efficient queries and manage migrations.

• Containerise applications with Docker and deploy to AWS ECS (Fargate/EC2) and EC2.

• Build and maintain CI/CD pipelines for automated build, test, and deployment.

• Ensure application security, performance, and scalability across the stack.

• Write unit and integration tests; participate in peer code reviews and uphold coding standards.

• Collaborate with product, QA, and infrastructure stakeholders; contribute to estimation and Agile ceremonies.

• Troubleshoot and optimise across the stack — from database queries and API latency to browser rendering and deployment reliability.

Must-Have Skills

Backend

• Python — advanced proficiency (OOP, typing, async/await).

• FastAPI — production experience building REST APIs; Pydantic models, dependency injection, OpenAPI/Swagger.

• Databases — PostgreSQL/MySQL, ORMs (SQLAlchemy), migrations.

• Auth & Security — JWT, OAuth2, secure handling of secrets and data.

Frontend

• Next.js / React — production experience with functional components, hooks, SSR/SSG, and the App Router.

• JavaScript / TypeScript — strong command of modern ES features and typed development.

• HTML5 / CSS3 — responsive design and component styling (Tailwind CSS or similar).

Cloud & DevOps

• AWS — hands-on with ECS and EC2 deployment; familiarity with S3, RDS, IAM, CloudWatch.

• Docker — building and optimising container images; registry management (ECR).

• CI/CD — designing and maintaining pipelines (GitHub Actions, GitLab CI, Jenkins, or AWS CodePipeline).

Agentic AI / GenAI

• Experience integrating LLMs such as OpenAI, Anthropic, or AWS Bedrock into applications.

• Understanding of Agentic AI, AI agents, tool/function calling, and multi-step workflows.

• Experience with RAG, embeddings, vector databases, and knowledge retrieval.

• Familiarity with agent frameworks.

• Experience building AI chat/streaming interfaces using React/Next.js; AG-UI or similar frameworks is a plus.

General

• Version control — Git-based workflows (branching, pull requests, code review).

• Testing — PyTest, Jest / React Testing Library.

• Microservices and event-driven architecture.

Good-to-Have Skills

• Infrastructure-as-Code (Terraform or CloudFormation).

• Async Python, background processing, and message/task queues (Celery, SQS, Kafka).

• Caching with Redis.

• Kubernetes (EKS) and observability tooling (Prometheus, Grafana, ELK, Datadog).

• AWS certifications (Solutions Architect / DevOps Engineer).

Qualifications

• Bachelor's degree in Computer Science, Engineering, or equivalent practical experience.

• Demonstrable track record of shipping and operating full-stack applications in production.

Key Attributes

• Strong problem-solving skills and ownership mindset across the full stack.

• Clear communicator, comfortable collaborating across product, engineering, and infrastructure teams.

• Quality-focused, with attention to security, performance, and maintainability.

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