GenAI Full Stack Engineer / Fullstack AI Engineer

Role Title: GenAI Full Stack Engineer / Fullstack AI Engineer / Agentic AI Engineer / GenAI Engineer / AI Engineer – Agentic AIExperience: 4–8 yearsEngagement Type: Full-timeLocations: Ahmedabad, Noida, Gurgaon, Jaipur, Pune, Bengaluru, HyderabadTechnology 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, LangGraphRole SummaryWe 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 SkillsBackend
• 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.