Incubated and funded in stealth inside of KPMG Studio, with additional institutional investment by SYN Ventures, Cranium emerged in 2023 with a mission to secure the AI revolution by delivering the industry’s leading AI security and trust solution. Whether organizations are builders and/or consumers of AI, Cranium offers a comprehensive platform that enables complete security, compliance, and trust across the entire AI supply chain.
For more information, visit: https://www.cranium.ai/.
Incubated and funded in stealth inside of KPMG Studio, with additional institutional investment by SYN Ventures, Cranium emerged in 2023 with a mission to secure the AI revolution by delivering the industry’s leading AI security and trust solution. Whether organizations are builders and/or consumers of AI, Cranium offers a comprehensive platform that enables complete security, compliance, and trust across the entire AI supply chain.
For more information, visit: https://www.cranium.ai/.
What: Enterprise AI security, governance, and third-party risk platform
Origin: Spun out of KPMG Studio; emerged from stealth in April 2023
Founders / leadership: Jonathan Dambrot (CEO & Co‑Founder); Paul Spicer (Co‑Founder & VP, IT Security); Daniel Christman (Co‑Founder)
Funding: Seed plus Series A; reported total funding about $32M (Series A $25M)
Employees: ~52
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Company Overview
Problem Domain
AI security, AI governance, and third‑party AI risk management for enterprises
Founded
2023
Industry
Data Security Software Products
Funding Track Record
Seed- April 2023
$7 million
Seed funding reported at launch when the company came out of stealth
Series A- October 26, 2023
$25 million
Series A reported to include participation from KPMG LLP and SYN Ventures; reported to bring total funding to $32 million
Founders
What we do
Join the Team
AI Scientist
RemoteUS
Remote • US
AI Scientist
ENGINEERING / FULL-TIME / REMOTE
Vision
Our vision is to secure the AI revolution. As the adoption of AI continues to expand, AI systems are increasingly exposed to new classes of threats. Without visibility into the AI assets in use, or monitoring of key metrics and threat indicators, organizations will not be able to keep up with this changing landscape. Our enterprise product is built to integrate with existing AI systems and detect AI threats.
Advancing the state of AI is a collaborative process that requires unusually varied skills and perspectives. To that end, we have built a multidisciplinary team with increasingly diverse backgrounds. Together, we're building the future of secure and trustworthy AI.
About The Role
Cranium builds products to secure AI. We develop cutting edge AI/ML methods that push the state of the art in the field. As an AI Scientist, you will be responsible for designing, building, and deploying the AI solutions that power our core platform. You will architect sophisticated solutions that leverage large language models to detect threats, analyze AI systems, and provide actionable intelligence to our customers. You will collaborate with cross-functional teams, stakeholders, and management to develop AI-driven capabilities that align with our company's vision and goals. You will also have the unique opportunity to contribute to our overall engineering culture as an early member of the team.
As an AI Scientist, you will:
Design and implement agentic AI systems and APIs that integrate with customer AI infrastructure and detect security threats.
Build agent architectures including tool use, planning, memory, and multi-agent coordination to analyze complex AI/ML environments.
Minimum Qualifications:
Bachelor's degree in Computer Science, Machine Learning, Statistics, or related field.
3+ years of experience building and deploying AI systems in production environments.
Proven experience building agentic AI solutions using large language models
Strong expertise in prompt engineering, chain-of-thought reasoning, and tool-use patterns.
Strong programming skills in Python and familiarity with LLM frameworks
Experience with cloud platforms (Azure, AWS, or GCP) and containerization technologies.
Deep understanding of language model capabilities, limitations, and best practices for building reliable agent systems.
Preferred Qualifications:
PhD or Master's degree in Computer Science, Machine Learning, Statistics, or related field.
Experience building multi-agent systems or complex agent orchestration workflows.
We offer the opportunity to make a significant contribution to shaping the future of AI. This opportunity is a collaborative effort between impossibly talented individuals who share a passion for this mission. Our biggest asset is inclusion as we believe that building a diverse community is the key to succeeding on our mission. In addition to the goal and environment we offer:
Competitive salary, and company ownership through equity
Market-leading health, dental, and vision insurance for employees and dependents
Flexible Time Off Policy and Paid Parental/Family Leave
Education reimbursement program for Individual Learning
401(k) Retirement plan or RRSP Matching program
Teeming tracks opportunities at over 24,000 AI startups, then works with you to find (and land) the one you'll love.
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Develop robust pipelines for prompt engineering, retrieval-augmented generation (RAG), and agent orchestration.
Work with software engineers and product managers to integrate AI capabilities into customer-facing products.
Stay current with the latest advances in agentic AI, LLM applications, and prompt engineering techniques.
Experiment with novel agent architectures, reasoning strategies, and tool integration approaches to improve threat detection.
Evaluate and integrate new language models and AI capabilities as they become available.
Optimize AI services for performance, latency, and cost while maintaining quality and reliability.
Monitor and maintain AI services in production, ensuring reliability and performance.
Implement best practices for ML operations, including versioning, testing, and monitoring.
Familiarity with retrieval-augmented generation (RAG) and vector databases.
Experience with function calling, tool integration, and external API orchestration.
Knowledge of evaluation frameworks for agentic systems and LLM applications.
Understanding of fine-tuning techniques (LoRA, RLHF) and when to apply them.
Experience with A/B testing and experimentation frameworks for AI products.
Contributions to open-source LLM or agent frameworks.
Experience in cybersecurity, threat detection, or AI security domains.
Strong analytical and decision-making skills.
Good interpersonal skills, communication skills, and understanding of how to tie technical problems to business impact.
Familiarity with Agile or other project management methodologies.
