P99Soft - Software Developer - Python/Flask

Description :

About the Role

We are seeking a highly skilled professional with strong expertise in Software Development, AI, and Data Science, who can design, develop, and deliver intelligent, data-driven solutions for enterprise clients. The ideal candidate will have hands-on technical expertise, a deep understanding of AI and data engineering workflows, and the ability to interact directly with clients to define requirements, design architectures, and oversee delivery.

Key Responsibilities :

- Lead the design and architecture of AI and Data Science solutions aligned with business objectives.

- Define scalable technical frameworks for data ingestion, processing, model training, and deployment.

- Evaluate appropriate technologies, tools, and frameworks based on project scope and client requirements.

- Manage end-to-end delivery of AI, Data Science, or Software Development projects.

- Prepare detailed estimates, work breakdown structures, and project timelines.

- Ensure technical quality, adherence to standards, and timely delivery.

- Collaborate closely with cross-functional teams data engineers, data scientists, and software developers to ensure seamless execution.

- Act as a technical liaison and trusted advisor to clients.

- Conduct requirement-gathering sessions and translate business needs into technical deliverables.

- Provide regular updates, documentation, and presentations to stakeholders.

- Contribute to core development activities, particularly in areas such as:

- AI/ML model development and deployment (using frameworks like TensorFlow, PyTorch, scikit-learn, etc.)

- Backend development with Python, FastAPI, Flask, or Django.

- Data engineering workflows data pipelines, ETL, data lakes, and APIs.

- Mentor junior engineers and data scientists, providing guidance on technical and delivery aspects.

Technical Skills :

- Strong programming skills in Python.

- Knowledge of AI/ML lifecycle data preparation, model development, training, validation, deployment, and monitoring.

- Proficiency in Data Engineering concepts ETL pipelines, data wrangling, and data storage systems (SQL/NoSQL, cloud data warehouses).

- Experience with APIs and microservices (FastAPI, Flask, RESTful APIs).