AI Safety Engineer
1 week ago
About the Company:
OutcomeCatalyst is your data infrastructure partner for faster, smarter investment decisions. We help investment firms and capital markets teams automate the most painful parts of their data stack, from ingesting unstructured documents and onboarding third-party data to deploying AI-powered agents for research, modeling, and decision workflows. Whether you're a $100M hedge fund, a global investment bank, or anything in between, we build reusable, low-lift solutions that accelerate signal generation with zero disruption to your existing systems or processes. From automated data pipelines to front-end copilots, we help you scale insight with less overhead and more conviction.
About the Job:
We're building a dedicated AI safety function to ensure our AI systems align with human values and operate as intended. Reporting to the Head of Architecture, Engineering & Data, you will ensure AI systems are developed and deployed safely. You will work closely with engineers and stakeholders to integrate safety considerations throughout the AI development lifecycle.
Develop and implement safety and security protocols, monitoring systems, and tools to detect and mitigate potential harms.
Conduct risk assessments to identify hazards and vulnerabilities in AI systems.
Design and integrate safety-critical features directly into AI systems.
Build and maintain safety infrastructure including monitoring and management platforms.
Explore, and assist with compliance to, safety regulations and standards.
Investigate safety incidents, analyse root causes, and implement corrective actions.
Develop technical guardrails including input validation, output filtering, and hallucination detection.
Implement adversarial robustness testing and bias detection mechanisms.
Monitor AI system anomalies and performance drift.
Build RAG systems and validation frameworks for accurate AI outputs.
Collaborate with cross-functional teams throughout the AI development lifecycle.
Stay current with AI safety research and best practices Document safety protocols and maintain audit trails.
Train teams on AI safety and risk mitigation and contribute to organisational policies and governance frameworks.
Implement guardrail frameworks (Guardrails AI, NeMo Guardrails) to ensure safe AI operations.
About you:
Desirable skills and commercial experience  
Degree in Computer Science, Data Science, Engineering, or related field.
3-5 years' experience in machine learning, deep learning, and AI development.
Passionate about AI Safety, understanding safety principles, including risk assessment and hazard identification.
Experience with Large Language Models (LLMs), including fine-tuning and evaluation.
Experience with reinforcement learning safety, RAG systems, cloud platforms (AWS/GCP/Azure).
Excellent communication, collaboration, and interpersonal skills.
Proven ability to deliver in complex environments.
Financial services experience.
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