Senior hands‑on architect who owns technical direction and delivery execution for customer engagements building AI‑powered applications and digital platforms.
Compensation
The pay range for this position is $156000.00 - $234000.00/yr.
Responsibilities
Own architecture direction for agentic AI and full‑stack solutions across assigned engagements
Translate business and technical requirements into scalable, sustainable solution architectures
Set the architecture standards and design patterns delivery teams build against
Own code review and architecture review gates; make the final call on technical trade‑offs
Write production code for customer engagements
Requirements
Bachelor's degree in Computer Science, Engineering, Information Technology, or a related discipline
A senior hands-on architect who owns technical direction and delivery execution for customer engagements building AI-powered applications and digital platforms, leading distributed engineering teams.
Compensation
$156000 - $234000/yr
Responsibilities
Own architecture direction for agentic AI and full-stack solutions across assigned engagements
Translate business and technical requirements into scalable, sustainable solution architectures
Set the architecture standards and design patterns delivery teams build against
Own code review and architecture review gates; make the final call on technical trade-offs
Write production code for customer engagements approximately 40-60% of time
You will design and deliver hands-on AI training for enterprise clients. Sessions are mostly virtual and run in 3–4 hour blocks across global time zones.
Locations (3)
San Francisco Bay Area, California, United States
Dallas, Texas, United States
Washington, D.C., District of Columbia, United States
Responsibilities
Design and deliver hands-on AI training for enterprise clients
Facilitate virtual sessions ranging from executives to software engineers
Co-facilitate with other Metis trainers
Tailor content to each client’s industry, tools and security requirements
Keep content current as models, tools and pricing change quarterly
Design and execute end-to-end attacks against agentic systems, AI-enabled security products, orchestration frameworks, tools, plugins, connectors, identities, permissions and isolation boundaries.
Locations (2)
Redmond, Washington, United States
United States
Compensation
Research Sciences IC5 - The typical base pay range for this role across the U.S. is USD $142,800 - $274,800 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $188,000 - $304,200 per year.
Responsibilities
Design and execute end-to-end attacks against agentic systems, AI-enabled security products, orchestration frameworks, tools, plugins, connectors, identities, permissions and isolation boundaries.
Investigate indirect prompt injection, unsafe tool use, scope violations, privilege escalation, confused-deputy behavior, secret exposure, sandbox escape, cross-agent manipulation and tampering with human oversight.
Build realistic attack chains using attacker-controlled telemetry, alerts, code, web content and other inputs that agents encounter in production workflows.
Build systems that give defenders an advantage at a scale few engineering teams encounter, partnering with customer security teams and OpenAI’s product and research groups.
Responsibilities
Partner with customer security leaders and OpenAI’s Go-to-Market team to scope engagements, establish responsibilities, and define measurable success criteria.
Lead technical design and implementation alongside customer engineers. Integrate agents into security workflows, establish access boundaries, and determine which actions require human review.
Build evaluations grounded in the decisions defenders make. For a patching agent, test whether a fix blocks a known exploit while preserving expected application behavior. For a detection system, replay historical attacks alongside normal traffic to measure detection speed and false-positive rates.
Guide production rollout with the engineers who will operate the system. Provide the observability and controls they need to understand system behavior, intervene when necessary, and expand adoption with confidence.
Translate successful approaches across deployments into reusable tools and engineering practices that other defenders can adopt.
Founding technical leader to build and guide an AI red team with expertise across adversarial machine learning, agent security, offensive security, automation and privacy.
Compensation
The typical base pay range for this role across the U.S. is USD $165,600 - $296,400 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $220,800 - $331,200 per year.
Responsibilities
Build and develop a team of specialists spanning adversarial machine learning, agent security, offensive security, attack automation and privacy.
Set the attack strategy and severity bar for uncovering critical weaknesses in advanced AI models, agentic systems and AI-enabled products.
Lead hands-on red-team operations across models, training and evaluation systems, agent frameworks, tools, identities and permissions to discover exploitable behavior before release.
Design and operationalize high-fidelity attack campaigns, continuous adversarial testing and automated suites that reproduce realistic threats at scale.
Drive critical findings to verified remediation with research, engineering and product security teams, converting recurring weaknesses into regression evaluations, adversarial environments and stronger controls.
We are seeking an experienced security practitioner responsible for investigating AI-related security events and executing approved enforcement actions across enterprise AI use cases. This role supports a 24/7 operational security function and combines hands-on threat investigation, policy validation, evidence collection, and control tuning to reduce risk while enabling secure adoption of AI technologies.
Responsibilities
Triage and investigate alerts involving enterprise AI applications, LLMs, AI agents, plugins, skills, browser extensions, local IDE tooling, agent-to-agent traffic, and SaaS/PaaS attack surfaces.
Correlate telemetry from endpoint, network, cloud, SaaS/PaaS, identity, AI gateway, and application controls to determine scope, cause, and potential impact.
Execute documented enforcement actions such as blocking prohibited AI destinations or tools, restricting risky agent capabilities, escalating compromised identities, and recommending policy changes.
Validate detections and enforcement policies through controlled sandbox and adversarial testing, including prompt injection, impersonation, data leakage, unsafe tool use, and unauthorized model or agent access.
Maintain investigation of records, evidence, indicators, case timelines, and remediation actions in accordance with security operations procedures.
Requirements
Bachelor’s degree (B.E./B.Tech) in Computer Science, Cybersecurity, Information Technology or a related discipline
Master’s degree/Diploma in Cybersecurity or Network Security
Develop automated attack suites and high-fidelity test environments that continuously exercise model behavior, harness logic, tools, identity and representative product telemetry together.
Create rigorous threat models, attack hypotheses and reproducible evidence; assess exploitability, severity and customer or governance impact.
Requirements
Doctorate in relevant field
Master's Degree in relevant field
Bachelor's Degree in relevant field
Nice to have: hands-on expertise in offensive security
Practice Architect II-AI/MLTEKsystems · Remote, US
AI TrainerMetis Strategy · Remote, US+2 more
Forward Deployed Engineer (FDE), Cyber - SFOpenAI · San Francisco, US