Senior Applied AI Engineer
Tasks
- Automate testing
- Build RAG pipelines
- Build multi-agent workflows
- Build reliable scalable secure agents
- Create technical documentation
- Deliver client engagements with measurable business value
- Deploy and operate AI solutions
- Design agentic AI solutions
- Design prompt and context engineering
- Develop APIs
- Develop reusable accelerators and reference implementations
- Implement LLM evaluation and guardrails
- Implement human in the loop steps
- Implement observability for LLM systems
- Integrate agents with enterprise systems
- Operationalize production ready agentic systems
- Perform code reviews
- Translate requirements into production code
- Use tool function calling
- Write SQL queries
Perks/Benefits
Skills/Tech-stack
APIs | AWS Bedrock | Agent systems | AgentOps | Agentic Architectures | Amazon SageMaker | Azure AI | Cloud Computing | Context engineering | Evaluation | Function Calling | Generative AI | Guardrails | LLMOps | Langchain | Language Models | Large Language Models | Llamaindex | Multi-Agent | Multi-Agent Systems | Observability | Prompt engineering | Python | RAG | Retrieval-Augmented Generation | SQL | Security | Snowflake Cortex | Tool use
Education
N/A
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