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Job description
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 VP 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. We're looking for engineers fluent in modern AI application development — agent frameworks, harnesses, tool use, prompting, retrieval, and evaluation — not machine learning engineers. You will be expected to train foundation models / frontier models . You will compose capable, production-grade AI systems on top of frontier models, get them into people's hands, and bring the rigor to prove they actually work.
What you'll do
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.
Also be a part of the COE Consult team to help across the organization.
Document what you build and how it should be used, operated, and evaluated.
Qualifications
An AI Expert in Multi-agentic solutions.
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 SDKs (Claude, OpenA and Google), thorough understanding and use of 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 in security, or building AI for security use cases
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Worksite address
san francisco, CA, 94199, US
Who can apply
Review the original listing for work authorization, qualifications and employer requirements.