Senior Python Developer

Job Description:

• Hands-on Development & Technical Leadership

- Write clean, efficient, and scalable Python code for AI-driven applications (backend & front end).

- Actively contributes to core modules and critical components of the system.

- Guide the team members in solving complex coding challenges and debugging.

- Lead development efforts involving Generative AI, LLMs, RAG, Lang Chain, etc.

• Solution Design & Deployment

- Architect & design scalable, secure, and maintainable Python-based systems.

- Evaluate trade-offs in design decisions and document technical approaches.

- Develop modular & scalable architecture-based solutions on cloud (AWS/Azure). Must demonstrate strong experience in microservices & docker / Kubernetes deployment.

- Demonstrate use of advanced python concepts, multi-threading & multi-processing & guide team on the same.

- Design AI workflows and pipelines integrating ML models, LLMs and RAG.

• Scrum Master & Team Leadership

- Project Estimation & Planning - Collaborate with stakeholders to define scope, timelines, and resource needs.

- Break down requirements into actionable tasks (features & stories) and estimate effort accurately.

- Track progress and adjust plans to meet delivery goals.

- Facilitate agile ceremonies and foster a collaborative team culture.

• Code Review & Quality Assurance

- Conduct thorough code reviews to ensure adherence to coding standards.

- Promote best practices in design, coding, testing, documentation, and CI/CD.

- Mentor team members on architecture, deployment, design patterns, performance optimization, and clean code.

Minimum Qualifications and Experience:

• Bachelor's or Master's degree in computer science with 7+ years of Python development experience, with 2+ years in a leadership role.

Required Skills:

• Strong understanding of Python frameworks (FastAPI, Django, Flask) & advanced python concepts, multithreading & multiprocessing.
• Proven experience in estimation, architecture, design, and code reviews.
• Hands-on experience with Generative AI, LLMs (e.g., OpenAI, Hugging Face Transformers), and Lang Chain.
• Experience implementing RAG pipelines and retrieval-based AI systems.
• Experience with cloud platforms (AWS or Azure) and containerization (Docker, Kubernetes).
• Excellent communication and stakeholder management skills.
• Good to have - Experience with AI/ML libraries (Tensor Flow, PyTorch, Scikit-learn).
• Experience in deploying AI models to production.
• Exposure to MLOps tools and practices.
• Domain knowledge in fintech, NBFCs, or enterprise AI solutions.
• Contributions to open-source or technical publications.