Lead Backend AI Developer
3 days ago
Company Description
At StatusNeo, we are catalysts of transformation, empowering businesses through cutting-edge AI, automation, and cloud-first digital solutions. As experts in product & platform engineering, we deliver unparalleled user experience, design, and functionality. Our team consists of top-notch software engineers and product designers, handpicked from the industry's finest talent pool. Recognized for our innovation and collaboration, we have earned the prestigious Great Place To Work certification. Join StatusNeo and be a part of a culture that breeds success and excellence.
Responsibilities:
• 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.
Qualification Requirements:
Educational:
• Bachelor's degree with at least 7 years of experience or Master's with at least 4 years of experience in Computer Science, Software Engineering, Data Science, or related fields.
Technical:
• 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.
Other:
• 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.
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