LT
Job Description
Job Summary:
- Develop generative AI solutions on AWS, emphasizing prompt engineering for large language models (LLMs), retrieval-augmented generation (RAG), and agentic AI using n8n and Python libraries like LangChain.
Key Requirements:
- Build LLMs (e.g., Anthropic Claude) on AWS Bedrock with boto
- Finetune LLMs on AWS SageMaker using transformers and LoRA.
- Create prompts with LangChain for optimized LLM outputs.
- Develop RAG pipelines with AWS OpenSearch and LangChain.
- Build AI agents with Crewai or Autogen on AWS Lambda.
- Implement agentic workflows in n8n (e.g., n8n.io/workflows/62707).
- Deploy applications with Docker on Amazon ECS/EKS.
- Monitor performance with Amazon CloudWatch and wandb. Must-Have Skills:
- 5 years of Python experience with 2 years in GenAI and LLMs.
- Expertise in AWS Bedrock, SageMaker, Lambda, and boto3.
- Proficiency in transformers, LangChain, Crewai, Autogen, and wandb.
- Experience with n8n workflows, RAG, and prompt engineering. Preferred Skills:
- AWS certification as a Machine Learning Solutions Architect.
- Familiarity with llamaindex and n8n templates.