GenAI Architect (AWS) – Remote, Senior Lead

Quantiphi, Inc.; United States; Remote; USD 150,000 - 230,000; Full time

Job summary

Quantiphi, Inc. is seeking a GenAI Architect (AWS) to design scalable enterprise GenAI solutions using Bedrock, AgentCore, and RAG pipelines. You will lead architecture, guide teams, and contribute to development for high-performance, cost-efficient AI systems.

The role emphasizes hands-on engineering, model evaluation, and collaboration with data, platform, and application teams to deliver secure, scalable AI-powered applications in a remote US setting.

Qualifications

• 8+ years of hands-on experience in cloud ML on AWS.
• Hands-on AWS services experience.
• Experience with AWS SageMaker and Bedrock.
• Design agentic AI architectures with LangChain/Strand Agents.
• Experience with Amazon AgentCore for production AI apps.
• Architect and deploy scalable AI solutions on AWS (Lambda, Bedrock, Step Functions).
• Proficiency with LLM APIs and multi-model orchestration.
• Hands-on fine-tuning/optimizing LLMs.

Responsibilities

• Design GenAI solutions using AWS Bedrock and Agentcore.
• Define architectures for LLM-based apps, including RAG pipelines and workflows.
• Develop agentic AI workflows for multi-step reasoning and tool usage.
• Build and manage RAG pipelines with embeddings and vector databases.
• Integrate LLM capabilities into enterprise apps via APIs and backends.
• Optimize prompts for accuracy, relevance and performance.
• Collaborate with cross-functional teams for end-to-end delivery.
• Establish security, governance and responsible AI practices.

Skills

Cloud ML experience

AWS expertise

LLM integration

RAG pipelines

AgentCore experience

LangChain/Agent frameworks

Vector databases

Model evaluation

Tools

AWS Bedrock

SageMaker

Lambda

Step Functions

S3

API Gateway

LangChain

AgentCore

SageMaker Pipelines

Job description

Quantiphi, Inc. is seeking a GenAI Architect (AWS) to design scalable enterprise GenAI solutions using Bedrock, AgentCore, and RAG pipelines. You will lead architecture, guide teams, and contribute to development for high-performance, cost-efficient AI systems.

The role emphasizes hands-on engineering, model evaluation, and collaboration with data, platform, and application teams to deliver secure, scalable AI-powered applications in a remote US setting.