We are looking for a strong **Full Stack Developer with AI/ML experience** to design, develop, and maintain scalable enterprise applications.

The role requires strong hands-on expertise in **Python, FastAPI, Microservices, PostgreSQL, React/Angular, and Cloud technologies**, along with practical experience integrating **AI/ML and Generative AI capabilities** into business applications.

The ideal candidate will be a hands-on engineer who can work across the technology stack, develop production-grade applications, integrate AI capabilities, and take ownership of solutions from design through deployment and production support.

Key Responsibilities

Full Stack Development (Primary)

* Design and develop scalable backend services using **Python and FastAPI**.

* Design and implement **RESTful APIs and microservices**.

* Develop responsive and high-performance web applications using **Angular or React**.

* Build reusable frontend components and application frameworks.

* Design and optimize **PostgreSQL** databases, schemas, queries, indexes, and transactions.

* Integrate frontend applications with backend APIs and third-party services.

* Implement authentication, authorization, API security, logging, monitoring, and error handling.

* Troubleshoot and optimize application performance across the full technology stack.

* Participate in architecture and technical design discussions.

* Write unit, integration, and API tests.

* Participate in code reviews and establish engineering best practices.

AI/ML & Generative AI (Secondary)

* Integrate **AI/ML capabilities** into enterprise applications and business workflows.

* Develop or integrate machine learning models using **Python**.

* Work with ML libraries such as **scikit-learn, Pandas, NumPy, TensorFlow, or PyTorch**.

* Apply machine learning techniques such as classification, regression, clustering, and predictive modeling.

* Integrate **LLMs and Generative AI APIs** into applications.

* Develop AI-powered features using **prompt engineering, embeddings, RAG, and vector databases**.

* Expose AI/ML models and services through **FastAPI-based APIs**.

* Collaborate with Data Scientists and AI/ML Engineers to deploy models into production.

* Implement monitoring, logging, and performance optimization for AI-enabled applications.