Tom Cooper
I’m Tom Cooper, an AI and Machine Learning contractor with 15+ years across insurance, legal, and banking, as well as tech product environments.
About
I’m Tom Cooper, an AI and Machine Learning contractor with 15+ years across insurance, legal, and banking, as well as tech product environments. I specialize in taking AI initiatives from zero through to production in highly regulated settings—building teams from scratch, architecting ML platforms on AWS and GCP, and deploying LLM and multi-agent systems that deliver measurable business outcomes.
I’m also strongly focused on AI security, governance, and responsible adoption. I’ve founded an AI security council, led red teaming and adversarial testing for LLM-based applications, and helped organizations align with emerging regulatory expectations. I’m known for translating complex AI work for non-technical stakeholders and evangelising data science and AI adoption across organizations.
- 14 years' experience
- Joined September 2026
Skills· 14
Languages
- EnglishFluent
Industry experience
- Financial Services
- Professional Services
- Software & Internet
- Financial Services
Work experience· 9 roles
Led ML and AI strategy and delivery, reporting to the CEO. Co-designed and delivered a three-day AI course for senior developers covering LLM capabilities and multi-agent patterns. Drove production deployment of AI-powered dynamic pricing by assessing model performance against live booking data and supporting launch materials. Built an ML pipeline for guest review analysis, including topic extraction, sentiment classification, and categorization to surface actionable insights for property owners. Designed and implemented a medallion (bronze/silver/gold) ETL architecture on the AWS data lake to enable structured analytics workflows.
Built cloud infrastructure and data engineering foundations from scratch on GCP. Designed and implemented GCP environments with VPC networking and IAM integrated with Google Workspace, and set up Cloud Run and Compute Engine across sandbox, development, and production. Built data pipelines using dbt and Python on BigQuery to establish underwriting platform data foundations. Founded the company’s AI Security Council, authored governance materials, defined security review processes for agentic AI tooling, and worked with external compliance consultants on AI regulation and risk management. Conducted security assessments (prompt injection, credential exposure, and supply chain vulnerabilities), ran LLM red teaming exercises, and defined remediation standards and guardrails. Evaluated and deployed AI coding tools in isolated compute with network controls and monitoring, and ensured independent penetration testing passed with zero critical/high findings. Delivered company-wide AI, ML, and
Founded the Data Science function and established a Center of Excellence, leading a team of 20 (60 across wider R&D). Drove AI adoption by translating technical capability into commercial value and securing executive buy-in. Built an agentic AI framework and delivered two proof-of-concepts that advanced to MVP, implemented on AWS using Bedrock Agent, Guardrails, and Lambda. Delivered transcription and dictation AI for legal and banking use cases including speaker diarization and command handling using OpenAI, NVIDIA, and Claude Sonnet. Automated job estimation (LLM instruction extraction + XGBoost regression) and real-time job allocation (Prophet forecasting + linear programming with PuLP). Performed red teaming and adversarial testing across all AI applications (prompt injection, jailbreak attempts, hallucination assessment, and data leakage). Ensured production AI passed independent penetration testing with zero critical/high findings. Designed and delivered training programs on data
Education
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