AI engineer
Tasks
- Add runtime guardrails
- Add tracing with OpenTelemetry
- Build LLM powered features
- Connect features to SQL stores
- Design prompt eval sets
- Develop AI microservices in Python
- Implement RAG retrieval workflows
- Implement search with Elasticsearch
- Instrument latency cost token usage
- Integrate features with data vault vector database
- Integrate multi provider LLMs
- Integrate with Kafka message brokers
- Optimize cost latency quality
- Orchestrate prompts and tool calls
- Perform code reviews and debugging
- Prototype with AI coding assistants
- Write tested observable code
Perks/Benefits
Skills/Tech-stack
AKS | AWS | Agentic Workflows | Azure | Azure DevOps | Bicep | Bitbucket Pipelines | CI/CD | Cloud platform | Docker | Elasticsearch | Function Calling | GitHub Actions | Google Cloud | Google Cloud Platform | Kafka | Kubernetes | Language Models | Large Language Models | Linux | MLflow | OpenSearch | OpenTelemetry | PGVector | Pinecone | PostgreSQL | Prompt engineering | Prompt orchestration) | Python | Qdrant | Retrieval-Augmented Generation | SQL | Shell | Splunk | Terraform | Tool use | Vector Databases
Education
N/A
Roles
AI | AI Engineer | Engineer | Learning Engineer | Machine Learning Engineer
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