Senior AI Engineer
Tasks
- Apply Responsible AI and security-by-design
- Architect production grade LLM applications
- Build and optimize RAG pipelines
- Collaborate on AI architecture and strategy
- Design backend services and APIs for AI inference
- Develop agentic workflows with tool calling
- Implement LLMOps and GenAIOps evaluation and monitoring
- Mentor peers and establish best practices
- Optimize latency cost scalability and reliability
- Set up CI CD pipelines and model version management
Perks/Benefits
- Career growth
- Continuous experimentation
- Continuous learning
- Inclusive culture
- Remote-first flexibility
Skills/Tech-stack
Amazon Bedrock | BM25 | CI/CD | ChromaDB | Distributed Systems | Django | Docker | Elasticsearch | Embeddings | Evaluation Frameworks | Event Driven | Event-driven architecture | FastAPI | Hybrid search | Kubernetes | LLMOps | MLOps | Microservices | Monitoring | OpenAI | Pinecone | Prompt engineering | Python | Qdrant | Retrieval-Augmented Generation | Vector Databases | Vector Search
Education
N/A
Roles
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