Member of Technical Staff, Trust & Safety Engineer

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Member of Technical Staff, Trust & Safety Engineer based in Spain.

This is a high-impact engineering role focused on ensuring that advanced generative AI systems are safe, reliable, and aligned with responsible usage at scale. You will work at the intersection of machine learning, platform infrastructure, and policy enforcement, helping shape how next-generation AI models are deployed safely to millions of users. The role involves designing and implementing safety systems, building red-teaming frameworks, and translating ambiguous and evolving trust & safety challenges into robust technical solutions. You will collaborate closely with product, research, legal, and policy teams, contributing directly to both pre-launch safeguards and post-launch monitoring. Operating in a fast-moving environment, you will help define best practices where none yet exist, playing a critical role in shaping the safety foundation of cutting-edge AI technology.

• 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 event data, abuse detection, or behavioral signals.
• Ability to translate ambiguous policy, safety, or compliance requirements into clear technical implementations.
• Strong collaboration and communication skills, especially when working with legal, policy, research, and product stakeholders.
• Experience designing or supporting evaluation systems, red-teaming frameworks, or model safety testing is a plus.
• Comfort working in high-ambiguity environments where processes and solutions are still being defined.
• Strong written communication skills with the ability to document technical decisions and trade-offs clearly.
• Open-minded, proactive, and highly collaborative approach to engineering work.
• Interest in AI safety, generative models, or responsible AI deployment is strongly preferred.

Benefits

• Competitive compensation package ranging from $240K – $290K (based on experience and location adjustments).
• Opportunity to work at the forefront of generative AI and world-model simulation technology.
• Remote-first flexibility across Europe and the US, with optional access to major tech hubs.
• High-impact role shaping safety systems used by millions of users globally.
• Collaborative environment working closely with leading researchers, engineers, and policy experts.
• Strong ownership culture with autonomy to define systems and safety approaches from the ground up.
• Exposure to cutting-edge AI infrastructure, including LLM-based safety systems and large-scale simulation models.
• Inclusive and mission-driven engineering culture focused on responsible AI development.
• Opportunity to work on foundational problems in AI safety, evaluation, and system reliability.