Professional Overview
Physicist by training, technical leader by trade, now building agentic systems full time. Ten years across real-time trading infrastructure, applied ML at scale, and multi-agent automation running in production, including four years leading an ML consulting practice. Equally at home leading a team and in the codebase. Based in Lisbon
Experience
AI Expertise
Skills
Employment Type
Description of Responsibilities
- Built agentic document pipelines: intake, extraction, validation, routing
- Delivered an autonomous multi-agent pricing engine for a freight client
- Scoped and architected client engagements end to end, then shipped them
- Built a multi-agent system in Rust from scratch, orchestration to guardrails
AI Expertise
Skills
Employment Type
Description of Responsibilities
- Led senior engineers running the bank's critical trading infrastructure
- Built high-throughput, low-latency pipelines for live equity market data
- Owned credit-risk ML in production: deployment, monitoring, interpretability
- Built the firm's BI platform and consolidated firm-wide data
- Bridged trading, credit, compliance and data science on delivery
Key Achievements / KPIs
- Scaled credit-risk modelling from a handful of firms to all US equities
- Opened and led the firm's first AI work across its business lines
- Enabled major commission growth without adding headcount
AI Expertise
Skills
Employment Type
Description of Responsibilities
- Owned the firm's ML strategy and built the practice from scratch
- Led engineering teams delivering applied ML into client operations
- Ran a multi-year public sector ML programme from green field to production
- Represented ML capability to clients and internal leadership
Key Achievements / KPIs
- Grew ML from a small specialism into a core part of the offering
- Programme became the firm's reference case for applied ML
Education
Field of Study: MBA
Field of Study: High-Performance Computing
Field of Study: Computational Physics
Areas of Expertise
AI & Machine Learning Engineers
Design, train, and ship production ML models — from data pipelines to model inference at scale. Covers supervised learning, neural networks, LLM integration, and model optimisation.
AI Product & Strategy
Translate AI capabilities into product roadmaps, define success metrics, and drive adoption across engineering and business teams.
AI Business, Marketing & Strategy
Apply AI to marketing automation, content generation, customer segmentation, and revenue growth strategies.
