We are seeking a highly skilled Senior AI Backend Engineer to design, build, and scale backend systems that power AI-driven products. You will work at the core of our AI infrastructure, integrating machine learning models, optimizing inference performance, and building reliable APIs and data pipelines.

Tech Stack:

Python (preferred) or Node.js / Go
RESTful APIs and/or GraphQL
ML frameworks (TensorFlow, PyTorch, etc.)
Cloud platforms (AWS, GCP, or Azure)
SQL and NoSQL databases
Docker and containerization
Key Responsibilities:

Design and develop scalable backend services that support AI-powered applications.
Build and maintain APIs for model inference (LLMs, NLP, computer vision, recommendation systems).
Deploy and manage machine learning models in production environments.
Develop data pipelines for training, evaluation, and real-time inference.
Optimize system performance for low-latency, high-throughput AI workloads.
Implement monitoring, logging, and observability for AI services.
Ensure system security, reliability, and scalability.
Collaborate with ML engineers to productionize research models.
Work with DevOps to manage cloud infrastructure and CI/CD pipelines.
Required Skills:

Strong proficiency in Python (preferred) or Node.js / Go
Experience with ML frameworks (TensorFlow, PyTorch, etc.)
Experience deploying models to production environments
Experience in RAG, LLM and Agentic AI
Familiarity with cloud platforms (AWS, GCP, or Azure)
Strong understanding of databases (SQL and NoSQL)
Experience with Docker and containerization
Knowledge of distributed systems and microservices architecture

We are seeking a highly skilled Senior AI Backend Engineer to design, build, and scale backend systems that power AI-driven products. You will work at the core of our AI infrastructure, integrating machine learning models, optimizing inference performance, and building reliable APIs and data pipelines.

Tech Stack:

Python (preferred) or Node.js / Go
RESTful APIs and/or GraphQL
ML frameworks (TensorFlow, PyTorch, etc.)
Cloud platforms (AWS, GCP, or Azure)
SQL and NoSQL databases
Docker and containerization
Key Responsibilities:

Design and develop scalable backend services that support AI-powered applications.
Build and maintain APIs for model inference (LLMs, NLP, computer vision, recommendation systems).
Deploy and manage machine learning models in production environments.
Develop data pipelines for training, evaluation, and real-time inference.
Optimize system performance for low-latency, high-throughput AI workloads.
Implement monitoring, logging, and observability for AI services.
Ensure system security, reliability, and scalability.
Collaborate with ML engineers to productionize research models.
Work with DevOps to manage cloud infrastructure and CI/CD pipelines.
Required Skills:

Strong proficiency in Python (preferred) or Node.js / Go
Experience with ML frameworks (TensorFlow, PyTorch, etc.)
Experience deploying models to production environments
Experience in RAG, LLM and Agentic AI
Familiarity with cloud platforms (AWS, GCP, or Azure)
Strong understanding of databases (SQL and NoSQL)
Experience with Docker and containerization
Knowledge of distributed systems and microservices architecture