Design and architecture of ML solutions and GenAI/Agentic AI patterns
Experience with Bedrock, SageMaker, and Agentic AI (strands, AgentCore, LangGraph) including guardrails and GenAI security
Knowledgebase, RAG, prompt engineering and prompt optimization
Proven ability to deploy and scale ML/GenAI solutions to production in cloud-based MLOps environments (including Lambda, Step Functions, CloudWatch, CloudTrail)
Requirements:
Build and deploy end-to-end ML and Generative AI solutions
Develop ML/GenAI models, perform data analysis, and derive actionable insights
Scale AI solutions in production using cloud platforms and MLOps practices
Design architecture patterns for GenAI/Agentic AI and implement guardrails and security for GenAI solutions
Job description
This is a remote position.
We are looking for a Senior ML engineering expertise to build and deploy end-to-end AI solutions. The role involves developing machine learning and generative AI models, performing data analysis, and scaling solutions in production using cloud and MLOps practices.
Requirements
Design and Architecture of ML solutions
Architecture patterns for GenAI and Agentic AI solutions
Demonstrable strong experience with Bedrock, Sagemaker, Agentic AI (strands, AgentCore, LangGraph). Guardrails and security of GenAI Solutions
Demonstrable strong experience with Knowledgebase, RAG, prompt engineering, prompt optimization
Demonstrable strong experience in deploying and scaling ML/GenAI solutions to production environment
Comfortable with supporting services such has Lambda, State machines, Cloudwatch, Cloudtrail etc.
