
Chief AI Innovation Officer
2 weeks ago
Drive the advancement of responsible AI at a rapid pace.
- Prioritize and expedite AI safety services for customers, ensuring seamless deployment of new models and applications without compromising on safety.
- Establish industry benchmarks and best practices through scalable tools and clear guidelines that set the standard for AI safety.
- Optimize customer success by integrating safe and rapid innovation into customer workflows through intuitive tools and platforms.
The impact you'll make:
- Enable accelerated responsible innovation by providing world-class AI safety services that allow customers to deploy new models and applications quickly without compromising on safety.
- Influence the industry by establishing best practices, scalable tools, and clear benchmarks that set the standard for AI safety.
- Drive customer success through tools and platforms that integrate seamlessly into customer workflows, enabling safe and rapid innovation.
Key Responsibilities:
- Lead and inspire a team of AI engineers, platform engineers, and product managers:
- Set clear goals, mentor team members, and foster a culture of impact, collaboration, and rapid learning.
- Implement agile processes that prioritize speed without sacrificing quality or security.
- Collaborate closely with customers to understand and address their AI safety challenges:
- Engage directly with customer teams to understand their innovation objectives, pain points, and safety requirements.
- Translate customer needs into actionable roadmaps aligned with their innovation cycles.
- Deliver tools and services that ensure AI applications are aligned, robust, interpretable, and safe:
- Oversee the development of platforms for alignment assessments, adversarial testing, drift detection, and interpretability analysis.
- Make informed build vs. buy decisions to optimize speed and customer integration.
- Champion engineering excellence in a high-stakes environment:
- Establish and enforce secure coding practices, automation, monitoring, and infrastructure-as-code.
- Ensure system reliability through defined SLAs, SLOs, rigorous testing, and clear operational dashboards.
- Continuously innovate within AI safety methodologies:
- Keep current with cutting-edge research in AI safety, adversarial testing, and model evaluation.
- Pilot emerging techniques that enhance our offerings and accelerate customer deployments.
Requirements:
- 12+ years of experience in software engineering, with at least 5 years managing technical teams or complex projects.
- Proven track record delivering AI, ML, or data-intensive platforms or services (e.g., model evaluation platforms, MLOps systems, AI safety tools).
- Demonstrated success in team leadership, coaching, and talent development.
- Excellent cross-functional collaboration and communication skills, bridging technical concepts with customer value.
Technical Skills:
- Proficiency with common software languages, frameworks, and tools such as Python, TensorFlow, PyTorch, Docker, Kubernetes, JavaScript, HTML/CSS, REST APIs, and SQL/noSQL databases.
- Expertise with cloud environments such as AWS, GCP, or Azure.
- Familiarity with LLM architectures, including evaluation techniques, prompt engineering, and adversarial testing methodologies.
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