AI Engineer
Tasks
- Build RAG pipelines
- Create evaluation suites for agents
- Curate prompt and test datasets
- Debug end to end system failures
- Define success metrics
- Deploy and operate AI services
- Design and build agentic systems
- Develop LLM-powered agents
- Document designs and runbooks
- Establish CI/CD pipelines for AI services
- Implement orchestration logic
- Integrate external tools and services
Perks/Benefits
- N/A
Skills/Tech-stack
Adapters | Agent Development Kit | Agent systems | Amazon Web Services | CI/CD | Chroma | Cloud deployment | Cloud platform | Container Orchestration | Content Filtering | Data Modeling | Datadog | Deep learning | Docker | Fine Tuning | GRPC | Git | Google Agent Development Kit | Google Cloud | Google Cloud Platform | Grafana | Human-in-the-loop | Instruction Tuning | Integration Testing | JAX | Langchain | Langgraph | Language Models | Large Language Models | Llamaindex | Machine Learning | Microsoft Azure | Multi-Agent | Multi-Agent Systems | Observability | OpenTelemetry | PGVector | Pinecone | Prometheus | Prompt engineering | PyTorch | Python | RAG | REST API | Retrieval-Augmented Generation | SQL | SQL Data | SQL Data Modeling | Safety Guardrails | Scikit-learn | State machines | TensorFlow | The Loop | Unit Testing | Vector Databases | Weaviate | Web Services
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
Roles
AI | AI Engineer | Engineer | Learning Engineer | Machine Learning Engineer
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