Backend GenAi Engineer
Tasks
- Build RAG pipelines
- Build distributed systems for real time data
- Build evaluation observability and safety for LLMs
- Collaborate with product and design
- Deploy services on AWS and Kubernetes
- Design AI native microservices
- Design and optimize SQL and NoSQL data stores
- Develop multi-agent systems
- Ensure robustness security and high availability
- Implement API design for production systems
- Implement embedding pipelines
- Implement tool calling workflows
- Integrate multimodal models
- Optimize retrieval prompt orchestration latency and cost
- Translate video into structured form
Perks/Benefits
- N/A
Skills/Tech-stack
API Design | AWS | Agentic Workflows | Autogen | CI/CD | CrewAI | Distributed Systems | Docker | Embeddings | Kubernetes | LLM Observability | LLM safety | Langchain | Microservices | Milvus | Multimodal AI | NoSQL | Node.js | PGVector | Pinecone | Prompt engineering | Python | RAG | Retrieval-Augmented Generation | SQL | Stateful workflows | Tool-Calling | Vector Databases | Vision Models | Weaviate
Education
N/A
Roles
AI Engineer | Backend | Backend AI Engineer | Backend Engineer | Engineer
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