Key Responsibilities:

Develop, deploy, and maintain Python-based APIs and AI applications using FastAPI.
Build and optimize Generative AI workflows using frameworks like LangGraph and Vector databases.
Implement traditional ML and Deep Learning models for various AI tasks using PyTorch, TensorFlow, or Scikit-learn.
Integrate LangChain or other AI/ML orchestration frameworks into production systems.
Collaborate with data scientists, ML engineers, and product teams to design AI solutions and deploy ML models at scale.
Ensure high-quality, well-documented, and maintainable code following best practices.
Optimize performance, scalability, and reliability of AI applications and APIs.
Participate in code reviews, design discussions, and architecture decisions for AI/ML systems.

Required Skills & Qualifications:

Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or related field.
3–8 years of professional experience in Python development.
Strong experience with FastAPI for building high-performance APIs.
Hands-on experience with Generative AI frameworks like LangGraph, and Vector databases (e.g., Pinecone, Milvus, Weaviate).
Experience in traditional ML and Deep Learning frameworks such as PyTorch, TensorFlow, or Keras.
Familiarity with LangChain or similar AI orchestration frameworks.
Solid understanding of AI/ML model deployment, API integration, and performance optimization.
Experience with cloud platforms (AWS, Azure, GCP) for AI/ML deployment is a plus.
Strong coding, debugging, and problem-solving skills.

Good to Have:

Exposure to NLP/LLM projects or Generative AI pipelines.
Knowledge of containerization and orchestration (Docker, Kubernetes).
Experience with data preprocessing, feature engineering, and data pipelines for AI/ML workloads.
Familiarity with version control (Git) and CI/CD pipelines.

Soft Skills:

AI/Ml Developer

Backend Developer (AI/ML)