Pay Rate Range: $53.57 - 55.14/hr. Role Name - AI Engineering + AWS Bedrock
Job Description: Questions below need to be answered and submitted on the resume.
How does agentic AI differ from traditional AI?
What are the main components of an AI Agent?
What is the control loop in an AI agent?
What is planning in Agentic AI?
How do agents avoid conflicts?
Agent Development. Design| build| and deploy autonomous AI agents capable of reasoning| decision-making| and task execution. Use frameworks and tools such as LangChain| Semantic Kernel| or custom orchestration layers to create multi-step| multi-tool agents.
Prompt EngineeringoCraft and optimize high-quality prompts to improve the reliability and effectiveness of generative AI outputs. Develop prompt chains| system prompts| and context strategies for dynamic agent behavior. Continuously test and iterate prompts based on use case feedback and model performance.
Amazon Bedrock DevelopmentoBuild and deploy generative AI solutions using Amazon Bedrock with models from providers like Anthropic (Claude)| Cohere| Stability AI| and Amazon Titan. Use Bedrock features such as Guardrails| Knowledge Bases| and model customization to enhance AI agent safety and capabilities.
GenAIAgenticAI use case leveraging Amazon Q for business and the upcoming Amazon QuikSuite as a platform
Essential Skills: Proven experience in building autonomous AI agents using frameworks like LangChain or Semantic Kernel. Strong prompt engineering skills| including prompt design| chaining| and optimization for LLMs. Hands-on expertise with Amazon Bedrock| including model integration| Guardrails| and Knowledge Bases. Proficient in Python| API integration| and working with vector databases (e.g.| FAISS| Pinecone).Solid understanding of LLM behavior| RAG architecture| and deploying AI solutions on AWS cloud.
Skills: Digital : Python~Digital : Amazon Web Service(AWS) Cloud Computing~Digital : PySpark Experience Required: 6-8 years