Autonomous AI Architect for GenAI & LLM Solutions

Siri InfoSolutions Inc; Arden Hills (MN); On-site; USD 165,000 - 248,000; Part time

Job summary

Siri InfoSolutions Inc. is seeking an AI Architect Engineer to design, develop, and deploy advanced AI/GenAI solutions onsite in Arden Hills, MN. The role supports architects and delivery teams across enterprise use cases, with 8–10 years IT experience and 6+ years in AI/ML, including GenAI and LLM-based deployments.

Responsibilities include building autonomous AI agents, integrating systems via APIs, and optimizing performance, latency, and cost while ensuring robust monitoring and governance.

Qualifications

• Proficient in Python and REST APIs.
• Experience with LangChain, LangGraph, and CrewAI.
• Experience with AWS Bedrock and SageMaker.
• Familiar with AWS Lambda, Step Functions, EventBridge, and CloudWatch.
• Knowledge of vector databases, data preprocessing and ML fundamentals.
• Experience implementing Agentic AI and knowledge graphs.

Responsibilities

• Design and implement Agentic AI solutions using AWS cloud-native services.
• Build autonomous AI agents capable of planning, reasoning, memory management & tool execution.
• Integrate AI agents with enterprise systems through APIs, databases, event-driven architectures and microservices.
• Develop RAG pipelines and knowledge assistants; implement prompt engineering and evaluation frameworks.
• Fine-tune or optimize AI model performance, latency, scalability & costs; implement monitoring and observability.
• Support AI testing, validation and deployment.

Skills

Python programming

Rest APIs

AI/GenAI expertise

Tools

Python

LangChain

LangGraph

CrewAI

Amazon Bedrock

SageMaker

AWS Lambda

Step Functions

EventBridge

CloudWatch

Vector databases

Prompt Engineering

Knowledge graph integration

Job description

Siri InfoSolutions Inc. is seeking an AI Architect Engineer to design, develop, and deploy advanced AI/GenAI solutions onsite in Arden Hills, MN. The role supports architects and delivery teams across enterprise use cases, with 8–10 years IT experience and 6+ years in AI/ML, including GenAI and LLM-based deployments.

Responsibilities include building autonomous AI agents, integrating systems via APIs, and optimizing performance, latency, and cost while ensuring robust monitoring and governance.