Agentic AI Solutions Architect

Armis; Town of Texas (WI); On-site; USD 110,000 - 170,000; Full time

Benefits offered by this job

Job summary

Armis is seeking talented AI builders to join our Strategic Initiatives team as part of a new AI Center of Excellence. Designers will craft AI-native solutions—agents, assistants, and reusable skills—that advance our security mission and magnify the impact of teams across the company.

This builder role emphasizes hands-on AI application development—agent frameworks, harnesses, tool use, prompting, retrieval, and evaluation—rather than traditional ML engineering.

Qualifications

• Experience delivering real AI solutions using agents, assistants, copilots, or skills.
• Hands-on familiarity with agent frameworks and SDKs.
• Strong evaluation discipline with metrics and safety/reliability checks.
• Proficiency in Python and integrating cloud services with containers.
• Degree in CS/Engineering or equivalent professional experience.

Responsibilities

• Design, build, and productionize AI agents, assistants, and reusable skills.
• Turn ideas into MVPs and partner with engineering to productionize.
• Define and measure success with rigorous evaluation.
• Create secure, agentic workflows with guardrails and controls.
• Select and evaluate frameworks, tools, and models for the COE.
• Contribute to the COE Consult team across the organization.
• Document usage, operation, and evaluation procedures.

Skills

AI agent systems

Real AI solutions

Agent frameworks & SDKs

Evaluation discipline

Python programming

Cloud integration (AWS/Azure/GCP)

Education

Bachelor's or Master's in CS/Engineering or related field

Tools

Docker

Kubernetes

APIs integration

Job description

Armis is seeking talented AI builders to join our Strategic Initiatives team as part of a new AI Center of Excellence. Designers will craft AI-native solutions—agents, assistants, and reusable skills—that advance our security mission and magnify the impact of teams across the company.

This builder role emphasizes hands-on AI application development—agent frameworks, harnesses, tool use, prompting, retrieval, and evaluation—rather than traditional ML engineering.