Description:

- Design, develop, and maintain backend services and APIs to support AI/ML applications at scale.

- Productionize ML and deep learning models, ensuring efficiency, reliability, and low-latency inference.

- Build scalable microservices and REST/gRPC APIs for deploying AI solutions in enterprise environments.

- Optimize AI model serving using frameworks such as TensorRT, ONNX Runtime, Triton Inference Server, or FastAPI.

- Implement MLOps practices including model versioning, monitoring, and automated deployments.

- Collaborate with AI researchers, data scientists, and product managers to translate prototypes into production-ready systems.

- Ensure robustness, fault tolerance, and security in backend AI systems.

- Integrate AI services with enterprise data platforms, cloud systems, and third-party APIs.

- Contribute to architecture discussions, design reviews, and performance tuning.

- Mentor junior engineers and contribute to best practices in AI software engineering.

Educational & Experience requirements :

- Bachelors degree with at least 7 years of experience or Masters with at least 4 years of experience in Computer Science, Software Engineering, Data Science, or related fields.

- Preferred to have degree from a Tier-1/2 institute (IIT/IISc/NITs if studied in India) or a globally top-ranked university (as per QS).

Technical Requirements :

- Strong proficiency in Python and backend frameworks (FastAPI).

- Expertise in Prompt engineering and working with various LLMs.

- Experience in productionizing AI/ML models with efficient inference pipelines.

- Hands-on experience with model deployment frameworks (Triton, TensorRT, TorchServe, ONNX Runtime).

- Knowledge of cloud platforms (Azure, GCP) and container technologies (Docker).

- Strong experience with microservices architecture, CI/CD pipelines, and monitoring tools (Prometheus, Grafana).

- Familiarity with databases (SQL/NoSQL) and scalable data storage solutions.

- Exposure to LLMs, SLMs, and GenAI model integration into backend systems is a strong plus.

- Understanding of security, authentication, and performance optimization in large-scale systems.

- Experience with version control (Git) and Agile development practices.

Behavioral Requirements:

- Excellent problem-solving skills and attention to detail.

- Strong written and verbal communication skills in English.

- Ability to work collaboratively in cross-functional teams.

- Passion for building reliable backend systems that bring AI models into real-world impact.