
AI-Powered Backend Developer
1 week ago
About the Role
We are seeking a skilled Backend Software Engineer to design, build, and scale backend services for our global art information platform. In this role, you will work on integrating advanced AI/ML models into production systems, powering features such as recommendations, personalization, and intelligent search.
This position is ideal for someone passionate about software engineering and excited to bring AI-powered user experiences to life at scale. Experience in recommendation systems is a strong advantage but not a strict requirement.
Responsibilities:
- Design, build, and maintain robust backend services using Python (FastAPI, Django, or Flask).
- Integrate machine learning models into production APIs and pipelines for recommendations and personalization.
- Collaborate closely with ML engineers and product teams to deliver AI-driven features.
- Develop low-latency APIs for serving recommendations and intelligent results.
- Work with vector databases (Qdrant, Pinecone, Elasticsearch, etc.) to power similarity search and embeddings.
- Deploy, monitor, and scale services in cloud environments (AWS preferred).
- Contribute to system architecture, performance optimization, and design decisions.
- Implement CI/CD pipelines with strong testing and code quality practices.
Requirements:
- Strong understanding of backend architecture and distributed systems.
- Proven track record of building and deploying production-ready APIs.
- Experience integrating ML models or AI services into backend infrastructure.
- Hands-on expertise with cloud platforms (AWS preferred) and DevOps tools (Docker, Kubernetes, Terraform).
- Database expertise: SQL (PostgreSQL/MySQL) and NoSQL (Redis, Elasticsearch).
- Excellent communication and collaboration skills in remote team settings.
Nice to Have (Bonus Skills):
- Experience with recommendation systems or personalization pipelines.
- Familiarity with vector databases and embedding-based search.
- Frontend integration knowledge (React, Next.js, GraphQL).
- Experience monitoring and optimizing ML-powered production systems (Prometheus, Grafana).
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