- Develop and deploy scalable AI-powered applications using the Python stack.

- Leverage cutting-edge AI/ML technologies such as LangChain, LangGraph, AutoGen, Phidata, CrewAI, Hugging Face, OpenAI APIs, PyTorch, TensorFlow, and other advanced frameworks to build innovative AI applications.

- Write clean, efficient, and well-documented code adhering to best practices.

- Build and manage robust APIs for integrating AI solutions into applications.

- Research and experiment with emerging technologies to discover new AI-driven use cases.

- Deploy and manage AI solutions in cloud environments (AWS, Azure, GCP), ensuring security, scalability, and performance.

- Collaborate with product managers, engineers, and UX/UI designers to define AI application requirements and align them with business objectives.

- Apply MLOps principles to streamline AI model deployment, monitoring, and optimization.

- Solve complex problems using foundational knowledge of generative AI, machine learning, and data processing techniques.

- Contribute to the continuous improvement of development processes and practices.

- Resolve production issues by conducting effective troubleshooting and root cause analysis (RCA) within SLAs.

- Work with operations teams to support product deployment and issue resolution.

Requirements :

Educational Background :

- Bachelor's or Master's degree in Computer Science or related fields with a strong academic track record.

Experience Technical Skills :

- 3+ years of hands-on experience in building and deploying AI applications on a Python stack.

- Strong knowledge of Python and related frameworks.

- Good knowledge of a few of the AI/ML frameworks and agentic frameworks and platforms like LangChain, LangGraph, AutoGen, Hugging Face, CrewAI, OpenAI APIs, PyTorch, and TensorFlow etc.

- Experience with AI/ML workflows, including data preparation, model deployment, and optimization.

- Proficiency in building and consuming RESTful APIs for connecting AI models with web applications.

- Knowledge of MLOps tools and practices, including model lifecycle management, CI/CD for AI, and model monitoring.

- Familiarity with cloud platforms like AWS, Azure, or Google Cloud, including containerization (Docker) and orchestration (Kubernetes).

- Experience with CI/CD pipelines, version control (Git), and automation frameworks.

- Strong understanding of algorithms, AI/ML fundamentals, and data preprocessing techniques.

Soft Skills :

- Passion for exploring, experimenting, and implementing emerging AI technologies.

- Self-starter who can work independently and collaboratively in a fast-paced environment.

- Excellent problem-solving and analytical abilities to tackle complex challenges.

- Effective communication skills to explain AI concepts and strategies to stakeholder