Python API Developer

1 week ago

Pune, Maharashtra, India pi-labs Full time ₹ 15,00,000 - ₹ 25,00,000 per year

Company Description

pi-labs provides cutting-edge cybersecurity and intelligence solutions to governments and enterprises, helping them stay ahead of emerging cyber threats driven by the rapid adoption of AI. We specialize in developing advanced tools that safeguard digital ecosystems and ensure trust, safety, and authenticity. Our flagship product,
Authentify
, is a market-leading deepfake detection solution designed to combat sophisticated AI-driven manipulations.

At pi-labs, you'll work with a team of passionate experts at the forefront of AI-powered security technologies. Join us to build impactful solutions, solve complex challenges, and contribute to protecting the digital world as it evolves.

Role Description

We are looking for a skilled Python developer with proven experience in designing and implementing scalable APIs. The candidate should have strong expertise in Python-based backend development and hands-on experience with various Inference servers.

Key Responsibilities


•Design, develop, and maintain high-performance and scalable APIs in Python.


•Implement APIs that interact with Inference servers


•Optimize API performance for real-time inference and large-scale workloads.


•Collaborate with ML engineers and data scientists to deploy and serve AI/ML models through Inference servers.


•Ensure API reliability, fault tolerance, and adherence to best practices in security and scalability.


•Develop automated tests, CI/CD pipelines, and monitoring solutions for APIs.


•Troubleshoot performance bottlenecks, integration issues, and production incidents.


•Write clean, well-documented, and maintainable code.

Required Skills & Qualifications


•3–5 years of professional experience in backend/API development.


•Strong proficiency in Python and frameworks like FastAPI / Flask / Django REST Framework.


•Solid understanding of RESTful API design principles and microservices architecture.


•Hands-on experience with various inference servers and their integration (vLLM, Triton).


•Familiarity with deploying AI/ML models into production environments.


•Experience with Docker, Kubernetes, or container orchestration tools.


•Strong grasp of scalability, concurrency, and distributed systems.


•Good understanding of API security (OAuth2, JWT, etc.).

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