Full Stack Developer(Python/AI)

Job Summary (List Format):

• Location: Noida
• Experience Required: 3 to 5 years

Key Responsibilities:

• Full stack development of end-to-end AI-enabled applications.
• Design and develop frontend using React (with reusable, responsive, high-performance components).
• Build backend services using FastAPI (Python).
• Create scalable, schema-flexible data storage solutions with MongoDB; design efficient schemas and indexing strategies.
• Develop secure, asynchronous RESTful and/or GraphQL APIs using FastAPI.
• Ensure seamless data flow between frontend, backend, and AI services.
• Integrate AI/ML models (LLMs, NLP, embeddings, recommendations, vision models) into existing systems.
• Build backend orchestration layers for model inference, prompt workflows, and vector search.
• Work with AI platforms (OpenAI, Azure OpenAI, AWS AI services, Hugging Face, or custom ML models).
• Optimize AI inference for latency, throughput, reliability, and cost.
• Design and maintain microservices-oriented backend architecture.
• Apply best practices for async programming, background tasks, API rate limiting, and caching.
• Implement authentication and authorization using OAuth2/JWT.

Required Skills & Qualifications:

• Frontend:
• Strong proficiency in React, TypeScript, HTML5, CSS3.
• Experience building complex, data-intensive UIs.
• Backend:
• Expert-level Python programming.
• Extensive hands-on experience with FastAPI (API design, async programming, performance tuning).
• Database:
• Advanced experience with MongoDB (schema design, indexing, aggregation pipelines).
• AI/ML:
• Practical experience integrating AI/ML or GenAI features.
• Understanding of embeddings, vector search, and model APIs.
• Cloud & DevOps:
• Experience with AWS, Azure, or GCP.
• Knowledge of Docker, CI/CD pipelines, infrastructure best practices.

Nice-to-Have / Preferred:

• Experience with vector databases (Pinecone, FAISS, Weaviate, MongoDB Atlas Vector Search).
• Hands-on GenAI experience.