Back-End Developer with AI Experience
Wing Assistant, Manila, Philippines
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The role
Wing is on the exciting mission of redefining the future of work for companies worldwide! We are looking to be the one-stop shop for companies that are looking to build world-class teams & place their operations on autopilot.
We are looking for a Back-End Developer with AI experience to design, build, and maintain server-side applications and services that power AI-driven solutions. The ideal candidate has strong expertise in back-end technologies, database management, and cloud infrastructure, combined with hands-on experience integrating and deploying AI/ML models and APIs.
What you will do
- Design, develop, and maintain scalable back-end systems, APIs, and
microservices.
- Integrate AI/ML models (NLP, computer vision, recommendation systems, etc.)
into production applications.
- Collaborate with front-end developers, AI/ML engineers, and data scientists to
deliver end-to-end AI-powered features.
- Optimize databases, APIs, and system performance to handle large-scale
data processing and real-time AI inference.
- Implement secure authentication, authorization, and data protection
practices.
- Build and manage data pipelines to support training, testing, and deployment
of AI models.
- Monitor, debug, and improve system reliability and AI feature performance.
- Stay current with emerging technologies in AI/ML, cloud services, and back-end frameworks.
What you need
Qualifications
•Bachelor’s degree in Computer Science, Software Engineering, or a related
field (or equivalent experience).
- Proven experience as a Back-End Developer (3+ years).
•Strong proficiency in at least one back-end language/framework (Node.js,
Python/Django, Java/Spring Boot, or Go).
•Hands-on experience integrating AI/ML APIs or deploying machine learning
models into production (e.g., TensorFlow, PyTorch, Hugging Face, OpenAI APIs).
- Experience with relational and non-relational databases (MySQL, PostgreSQL,
MongoDB, etc.).
- Familiarity with RESTful APIs, GraphQL, and microservices architecture.
- Knowledge of cloud services (AWS, GCP, or Azure) for deploying AI-enabled
applications.