Senior Lead, AI Engineering, GDBS
Tasks
- Apply caching batching and model routing
- Build retrieval-augmented generation pipelines
- Design and ship LLM powered features end to end
- Develop structured extraction and summarisation workflows
- Implement agentic tool using workflows
- Implement rigorous testing and pull request discipline
- Integrate AI layer with vector stores and source systems
- Mitigate hallucinations and improve reliability
- Optimize latency token usage and throughput
- Set up evaluation monitoring and guardrails
- Translate business problems into AI solutions
Perks/Benefits
Skills/Tech-stack
Authentication | Authorization | Batching | CI/CD | Caching | Cloud Run | Django | Docker | Embeddings | FastAPI | Flask | Function Calling | GCP | Hallucination mitigation | Kubernetes | LLM | LLM Evaluation | Langchain | Llamaindex | MLOps | Model routing | PGVector | PostgreSQL | Prompt engineering | PubSub | Python | Red Teaming | Retrieval-Augmented Generation | SQL | Structured Output | Token Throttling | Vector Search | Vertex AI
Education
N/A
Roles
AI | AI Developer | Developer | Engineer | Learning Engineer | Machine Learning Engineer
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