
AI Innovation Director
6 hours ago
Transform AI development through responsible innovation at scale.
The Impact You'll Make- Pioneer cutting-edge AI safety services that empower customers to deploy innovative models and applications swiftly.
- Establish industry benchmarks, scalable tools, and clear guidelines for AI safety excellence.
- Drive customer success by integrating safe and rapid innovation into customer workflows.
- Lead a high-performing team (AI engineers, platform engineers, product manager): Set goals, mentor team members, and foster impact-driven collaboration and learning.
- Implement agile processes prioritizing speed without compromising quality or security.
- Collaborate closely with customers to understand and address AI safety challenges:
- Engage directly with customer teams to comprehend their innovation objectives, pain points, and safety requirements.
- Translate customer needs into actionable roadmaps aligned with their innovation cycles.
- Deliver tools and services ensuring 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 high-stakes environments:
- Establish secure coding practices, automation, monitoring, infrastructure-as-code, and rigorous testing.
- Ensure system reliability through defined SLAs, SLOs, operational dashboards, and clear communication.
- Continuously innovate within AI safety methodologies:
- Stay current with leading-edge research in AI safety, adversarial testing, and model evaluation.
- Pilot emerging techniques enhancing our offerings and accelerating customer deployments.
- 12+ years of experience in software engineering, 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.
- Proficiency with common software languages, frameworks, and tools like Python, TensorFlow, PyTorch, Docker, Kubernetes, JavaScript, HTML/CSS, REST APIs, SQL/noSQL databases.
- Expertise with cloud environments such as AWS, GCP, Azure.
- Familiarity with LLM architectures, including evaluation techniques, prompt engineering, and adversarial testing methodologies.
Experience with platforms like LangChain, LangGraph; familiarity with distributed systems (Spark/Flink); knowledge of AI regulatory frameworks or secure deployment standards.
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