AI Backend Engineer

Sproxil is a global brand protection & consumer engagement solutions provider specialized in the provision of cutting edge advanced technology to combat counterfeiting, product theft and adulteration; as well as providing a platform for consumer engagement.We are seeking an experienced and technically skilled AI Backend Engineer to help build and optimize the infrastructure that powers our AI-driven applications

Key Responsibilities

• Design and implement scalable APIs and microservices for AI model deployment and data ingestion.
  

• Collaborate with ML engineers to integrate and serve machine learning models (e.g., via REST).
  

• Build and maintain data pipelines to support training and inference workflows.
  

• Manage and optimize model storage, versioning, and lifecycle in production.
  

• Ensure backend systems are performant, secure, and fault-tolerant.
  

• Automate and monitor AI service deployments using containerization and orchestration tools (e.g., Docker, Kubernetes).
  

• Implement logging, monitoring, and alerting for AI backend services.
  

• Participate in code reviews, architecture design, and performance tuning.
  

Requirements

• Experience: 6months - 1 years experience in backend development (NYSC and SIWES preferred)
  

• Education: Bachelor's degree in Computer Science or any related fields
  

• Proficiency in backend languages like Python, Node.js, Java, or Go.
  

• Experience with frameworks such as FastAPI, Flask, Django, or Express.
  

• Strong understanding of REST APIs, authentication (OAuth2, JWT), and data serialization formats (JSON).
  

• Familiarity with AI model serving tools (e.g., TensorFlow Serving, TorchServe, Triton Inference Server).
  

• Proficient in working with databases (SQL and NoSQL)
  

• Experience with Git, CI/CD pipelines, and container orchestration (Docker, Kubernetes).
  

Benefits

• Competitive salary and benefits package
  

• Collaborative and supportive work environment with an international team
  

• Flexible work arrangement
  

• Continuous learning and professional development