Generative AI Full Stack Engineer

Role Title : GenAI Full Stack Engineer

Experience : 4-8 years.

Engagement Type : Full-time.

Locations : Ahmedabad, Noida, Gurgaon, Jaipur, 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.

Celebal Technologies :

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.

Skills

Generative AI, Full Stack, Artificial Intelligence, AI Integration, AWS, Next.js, React.js, Python, FastAPI, LLM, RAG