Backend Engineer Generative AI (Infra)

As a Backend Engineer specializing in Generative AI infrastructure, your primary responsibility will be to design and develop scalable backend services to support AI and Generative AI workloads. You will play a crucial role in building and optimizing RESTful and GraphQL APIs for model inference, prompt processing, and data access. Additionally, you will create modular backend components for high-performance, scalable AI operations. Your collaboration with AI engineers for integrating and deploying Generative AI models will be essential, especially in implementing retrieval-augmented generation (RAG) pipelines using vector databases like Pinecone, Weaviate, FAISS, or Milvus. Optimizing AI model serving and inference with frameworks like TensorFlow Serving, TorchServe, FastAPI, or custom endpoints will also be part of your key responsibilities. Key Responsibilities: - Design and develop scalable backend services to support AI and Generative AI workloads - Build and optimize RESTful and GraphQL APIs for model inference, prompt processing, and data access - Create modular backend components for high-performance, scalable AI operations - Collaborate with AI engineers to integrate and deploy Generative AI models in production - Implement retrieval-augmented generation (RAG) pipelines using vector databases - Optimize AI model serving and inference with frameworks like TensorFlow Serving, TorchServe, FastAPI, or custom endpoints Qualifications Required: - Bachelor's or Master's degree in Computer Science, IT, AI, or a related field - Certifications in AI/ML, Cloud Architecture, or Backend Development are a plus The company is seeking a Backend Engineer with 1.5 to 3 years of experience in backend engineering, API design, and AI model integration, particularly in the realm of Generative AI applications. Your familiarity with languages such as Python, Node.js, and Java, along with backend frameworks like FastAPI, Flask, Django, Express.js, and Spring Boot is crucial. Experience with LLMs, diffusion models, transformer models, databases (PostgreSQL, MongoDB, etc.), vector databases, infrastructure tools (Docker, Kubernetes, etc.), monitoring tools, and API technologies is highly desirable. Additionally, soft skills such as problem-solving abilities, communication skills, attention to detail, and curiosity for emerging AI technologies are valued in this role.,