AI Engineer

Cowbell is signaling a new era in cyber insurance by harnessing technology and data to provide small and medium-sized enterprises (SMEs) with advanced warning of cyber risk exposures bundled with cyber insurance coverage adaptable to the threats of today and tomorrow. Championing adaptive insurance, Cowbell follows policyholders’ cyber risk exposures as they evolve through continuous risk assessment and continuous underwriting. In its unique AI-based approach to risk selection and pricing, Cowbell’s underwriting platform, powered by Cowbell Factors, compresses the insurance process from submission to issue to less than 5 minutes.

Founded in 2019 and based in the San Francisco Bay Area, Cowbell has rapidly grown, now operating across the U.S., Canada, U.K., and India. This growth was recently bolstered by a successful Series C fundraising round of $60 million from Zurich Insurance. This investment not only underscores the confidence in Cowbell’s mission but also accelerates our capacity to revolutionize cyber insurance on a global scale. With the backing of over 25 prominent reinsurance partners, Cowbell is poised to redefine how SMEs navigate the evolving landscape of cyber threats.

Cowbell is signaling a new era in cyber insurance by harnessing technology and data to provide small and medium-sized enterprises (SMEs) with advanced warning of cyber risk exposures bundled with cyber insurance coverage adaptable to the threats of today and tomorrow. Championing adaptive insurance, Cowbell follows policyholders’ cyber risk exposures as they evolve through continuous risk assessment and continuous underwriting. In its unique AI-based approach to risk selection and pricing, Cowbell’s underwriting platform, powered by Cowbell Factors, compresses the insurance process from submission to issue to less than 5 minutes.

Founded in 2019, Cowbell is based in the San Francisco Bay Area with employees across the U.S., Canada, U.K. and India and is backed by over 15 A.M. Best A- or higher rated reinsurance partners.

Position Overview:

Key Responsibilities

• Design and implement RAG-based systems, integrating LLMs with vector databases, search pipelines, and knowledge retrieval frameworks.
• Develop intelligent AI agents that automate tasks, retrieve relevant information, and improve user interactions.
• Work with APIs, embeddings, and multi-modal retrieval to enhance AI application performance.
• Optimize inference pipelines and improve LLM serving, fine-tuning, and distillation for efficiency.
• Stay ahead of the curve by researching and implementing state-of-the-art advancements in generative AI and retrieval techniques.
• Collaborate with stakeholders and cross-functional teams to understand business needs and develop impactful ML models and AI-driven automation solutions.
  
  
  

Minimum Qualifications

• Master's in Computer Science, Data Science, AI, Machine Learning, or a related field (or a Bachelor's degree with substantial experience).
• 5+ years of experience in machine learning, deep learning, and NLP for real-world applications.
• 1+ years of hands-on experience with LLMs and generative AI.
• Expertise in RAG architectures, vector search, and retrieval methods.
• Proficiency in Python and experience with LLM APIs (OpenAI, Hugging Face, Anthropic, etc.).
• Experience integrating LLMs into real-world applications (e.g., chatbots, automation, intelligent decision-making agents).
• Solid foundation in machine learning, statistical modeling, and AI-driven software development.
• Knowledge of prompt engineering, few-shot learning, and prompt chaining techniques.
• Strong software engineering skills, including experience with cloud platforms (AWS) and ML model deployment.
• Excellent problem-solving skills, communication abilities, and ability to work independently.
  
  
  

Preferred Qualifications

• Proficiency in PyTorch or TensorFlow for deep learning model development.
• Experience in LLM fine-tuning, model compression, and optimization.
• Familiarity with frameworks like LangChain, LlamaIndex, or Ollama.
• Experience with multi-modal retrieval systems (text, image, structured data).
• Contributions to open-source AI projects or published research in AI/ML.
  
  
  

Equal Employment Opportunity:

We are committed to equal opportunity in the terms and conditions of employment for all employees and job applicants without regard to race, color, religion, sex, sexual orientation, age, gender identity or gender expression, national origin, disability, or veteran status.

Cowbell is a leading innovator in cyber insurance, dedicated to empowering businesses to always deliver their intended outcomes as the cyber threat landscape evolves. Guided by our core values of TRUE—Transparency, Resiliency, Urgency, and Empowerment—we are on a mission to be the gold standard for businesses to understand, manage, and transfer cyber risk.

At Cowbell, we foster a collaborative and dynamic work environment where every employee is empowered to contribute and grow. We pride ourselves on our commitment to transparency and resilience, ensuring that we not only meet but exceed industry standards.

We are proud to be an equal opportunity employer, promoting a diverse and inclusive workplace where all voices are heard and valued. Our employees enjoy competitive compensation, comprehensive benefits, and continuous opportunities for professional development.

Cowbell is an E-Verify employer. E-Verify is a web-based system that allows an employer to determine an employee's eligibility to work in the US using information reported on an employee's Form I-9. The E-Verify system confirms eligibility with both the Social Security Administration (SSA) and Department of Homeland Security (DHS). For more information, please go to the USCIS E-Verify website.

For more information, please visit https://cowbell.insure/.

Cowbell Cyber does not permit the use of AI tools during any stage of our interview process. By submitting your application, you agree to complete all assessments and interviews without the use of generative AI assistance.