Company
Technology
MemberofTechnicalStaff,Trust&SafetyEngineer
Neural analysis suggests this role is
optimal for Mid candidates.
“Member of Technical Staff, Trust & Safety Engineer. Skills: AI Safety, Generative AI, Responsible AI. Act as Trust & Safety engineering partner. Support safe design of AI systems”
What You'll Achieve.
Ensure responsible deployment; Identify harmful outputs before release; Identify policy violations before release; Identify adversarial behavior before release; Improve safety performance across iterations; Detect abuse patterns at scale; Detect policy violations at scale
Industry & Context.
Translate ambiguous requirements; Develop technical solutions; Identify harmful outputs; Identify policy violations; Identify adversarial behavior; Detect abuse patterns; Detect policy violations; Troubleshoot infrastructure
What They're Looking For.
Must Have
3+ years software engineering experience, Python proficiency, TypeScript proficiency, Backend systems experience, Infrastructure experience, Distributed systems experience, Cloud environments experience, Ownership mindset, Design systems end-to-end, Build systems end-to-end, Operate systems end-to-end, Monitoring experience, Incident response experience, Backend services experience, Internal tooling experience, Data pipelines experience, Infrastructure debugging experience, Translate policy requirements, Translate safety requirements, Translate compliance requirements, Clear technical implementations, Collaboration skills, Communication skills, High-ambiguity environments experience, Written communication skills, Document technical decisions, Document trade-offs
Nice to Have
AWS experience, GCP experience, Familiarity with analytics systems, Familiarity with large-scale data infrastructure, Event data experience, Abuse detection experience, Behavioral signals experience, Designing evaluation systems experience, Supporting evaluation systems experience, Red-teaming frameworks experience, Model safety testing experience, Open-minded approach, Proactive approach, Highly collaborative approach, Interest in AI safety, Interest in generative models, Interest in responsible AI deployment
What You'll Do.
Act as Trust & Safety engineering partner
Support safe design of AI systems
Support launch of AI systems
Design safety infrastructure
Build safety infrastructure
Maintain safety infrastructure
Ensure responsible deployment of models
Develop red-teaming systems
Improve red-teaming systems
Identify harmful outputs
Identify policy violations
Identify adversarial behavior
Translate requirements into solutions
Implement technical controls
Build internal tooling
Build systems for content moderation
Build systems for policy enforcement
Build systems for abuse detection
Build systems for safety evaluation
Implement technical controls
Evaluate model behavior
Improve safety performance
Contribute to system reliability
Contribute to performance optimization
Contribute to logging
Contribute to monitoring
Contribute to incident response
Support development of data pipelines
Support development of analytical systems
Detect abuse patterns
Detect policy violations
Continuously improve engineering quality
Continuously improve robustness
Continuously improve maintainability
How You'll Work.
Team & Collaboration
Embedded within product teams; Embedded within research teams; Collaborate with legal teams; Collaborate with policy teams; Collaborate with product teams; Work with machine learning researchers; Work with stakeholders
Communication Scope
Written communication; Document technical decisions; Document trade-offs
Full Job Description
## Accountabilities Act as a core Trust & Safety engineering partner embedded within product and research teams, supporting safe design and launch of AI systems from early development through production monitoring. Design, build, and maintain safety infrastructure that ensures responsible deployment of generative AI models at large scale. Develop and continuously improve red-teaming systems to identify harmful outputs, policy violations, and adversarial behavior before production release. Translate ambiguous, evolving trust & safety requirements into concrete, scalable technical solutions and enforcement mechanisms. Build internal tooling and systems for content moderation, policy enforcement, abuse detection, and safety evaluation. Collaborate with legal, policy, and product teams to define safety rules, interpret guidelines, and implement technical controls. Work closely with machine learning researchers to evaluate model behavior and improve safety performance across iterations. Contribute to system reliability, performance optimization, logging, monitoring, and incident response for safety-critical infrastructure. Support the development of data pipelines and analytical systems to detect abuse patterns and policy violations at scale. Continuously improve engineering quality, robustness, and maintainability across safety-related codebases and systems. Requirements 3+ years of software engineering experience in production environments, with strong proficiency in Python and/or TypeScript. Experience building and maintaining backend systems, infrastructure, or distributed systems in cloud environments (AWS or GCP). Strong ownership mindset with the ability to design, build, and operate systems end-to-end, including monitoring and incident response. Experience working across the stack, including backend services, internal tooling, data pipelines, and infrastructure debugging. Familiarity with analytics systems or large-scale data infrastructure, ideally involving eve
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