AI Solutions Consultant ( Agentic & Harness Engineering)

About the role

Armis is seeking talented, motivated AI builders to join our Strategic Initiatives team as part of a new AI Center of Excellence. Reporting to the SVP of Strategic Initiatives, this team designs and ships AI-native solutions — agents, assistants, and reusable skills — that advance Armis's security mission and multiply the impact of teams across the company. This is a builder role for engineers fluent in modern AI application development — agent frameworks, harnesses, tool use, prompting, retrieval, and evaluation.

Responsibilities

• Design, build, and bring to production-ready models, AI agents, assistants, and reusable skills that solve real problems for Armis and its customers.
• Turn ideas into working MVPs fast, then partner with engineering to harden them into reliable, production-ready systems.
• Build evaluation into everything you ship — define what "good" means for each solution, measure it, and hold the bar. Due diligence through rigorous evals is non-negotiable, not an afterthought.
• Compose agentic workflows that are secure by construction, using secure harnesses along with appropriate isolation, guardrails, and controls.
• Select and integrate the right frameworks, tools, and models for each job, and turn what works into reusable patterns and best practices for the COE.
• Contribute to the COE Consult team to support initiatives across the organization.
• Document what you build and how it should be used, operated, and evaluated.

Requirements

• Demonstrated experience building real AI solutions — agents, assistants, copilots, or skills — that shipped and got used, not just prototyped.
• Deep, hands-on familiarity with modern agent frameworks and developer tooling (agent SDKs such as the top 3 providers: Claude, OpenAI, and Google), thorough understanding and use of the SKILL.md skills standard, plus the judgment to know which to reach for when.
• Strong evaluation discipline: building test sets, defining metrics, and measuring quality, safety, and reliability before and after deployment.
• Proficiency in Python and comfort integrating APIs, tools, and cloud services (AWS, Azure, or GCP) with containerization (Docker, Kubernetes).
• Bachelor's or Master's in Computer Science, Engineering, or a related field, or equivalent professional experience.

Preferred Experience

• Experience in security or building AI for security use cases.