Leonardo – Python, Golang, AWS

A UK government agency issuing passports nationwide, running a BI/MI platform with daily outages and processing times measured in weeks. Leonardo stabilised the platform, migrated it to serverless AWS, built a unified Databricks data layer and led the agency’s AI adoption with MCP-based LLM integrations and an AI-voice detection system. The outages stopped, and passport processing went from weeks to days.

• Stabilised a failing BI/MI infrastructure that was experiencing daily outages, restoring service reliability.
• Designed and delivered a unified data layer using Databricks, aggregating data from every step of the passport application journey.
• Introduced serverless architecture on AWS, migrating critical national infrastructure from on-premise to cloud.
• Pioneered AI adoption by building MCP server wrappers integrating AWS Glue, Databricks, and SageMaker-hosted LLMs.
• Delivered a fixed-cost workforce planning and performance solution that improved passport processing times from weeks to days.
• Engineered a real-time audio analysis system using custom ML pipelines to distinguish between human and AI-generated voices.

An independent consultancy delivering AI and cloud architecture for financial services and regulated public sector clients. Leonardo builds AI research platforms on AWS SageMaker and Bedrock, agentic RAG systems and MCP services that give AI agents access to authoritative financial data. Everything is designed with governance built in (MAESTRO, RAGAS, prompt-injection defence) so it can run in regulated environments.

• Delivered high-stakes AI and cloud architecture engagements for financial services and regulated public sector clients.
• Designed AI-native research platforms using SageMaker, Bedrock, Jupyter, and MCP architectures.
• Built agentic AI systems with RAG pipelines and semantic search via OpenSearch.
• Designed financial data connectivity solutions using Kinesis, Glue, Delta Lake, and Databricks.
• Designed regulated environment governance architectures aligned to MAESTRO, RAGAS, and prompt injection defence patterns.
• Implemented infrastructure as code using AWS CDK and Terraform.
• Designed a strategy aggregator for financial market analysis using NotebookLM, Qdrant, and Amazon Bedrock.
• Built early MCP services enabling AI agents to query authoritative financial data sources and share research outputs across teams.
• Designed and built a real-time audio analysis bot using custom ML pipelines to distinguish human from AI-generated voices.
• Invented and patented an AI system utilising Cascade Forward Artificial Neural Networks to optimise software execution thread allocation in high frequency trading applications.

A global investment bank’s electronic FX (eFX) trading business, whose high-frequency pricing engines needed to compete on latency with tier-one banks in co-location environments. Leonardo led the bank’s first eFX co-location project and built sub-millisecond data connectivity for pricing engines in London, New York and Tokyo. He also created an AI-driven performance tuning solution, later patented, that watched application threads on the servers and moved them to the CPU cores with the lowest latency. Algorithmic trading engine performance improved by 270%, latency spikes dropped 25x, and the eFX business could compete in co-location against tier-one investment banks.

• Led HSBC's first eFX co-location project, building the data connectivity foundation for high frequency pricing engines across London, New York, and Tokyo.
• Reduced latency spikes by 25x, improving the research-to-production path for pricing models across FX and equities.
• Built sub-millisecond data connectivity infrastructure ensuring researchers had real-time access to complex cross-asset market datasets.
• Optimised the end-to-end trading infrastructure across London, New York, and Tokyo simultaneously.
• Established the performance baseline that enabled HSBC's eFX business to compete effectively in co-location environments against tier-one investment banks.

The fixed income trading arm of a global investment bank, whose front-office trading platforms suffered recurring trading floor outages. Leonardo led a two-year recovery programme and designed the next-generation middleware platform for trading systems in London, New York and Tokyo. He also directed a global middleware upgrade across 40 applications and 7 business units, and introduced the bank’s first Linux-based application. The recovery programme stopped the outages and saved the bank over £10 million. The Linux move cut hardware CAPEX by 80% and raised platform performance by 400%, and infrastructure capacity grew 300% over three years with no service disruption.

• Led a two-year recovery programme that saved Barclays Capital over £10 million by eliminating trading floor outages across global front-office platforms.
• Directed a global middleware upgrade programme across 30+ engineers, 40 applications, and 7 business units.
• Introduced the bank's first Linux-based application, reducing hardware CAPEX by 80% and increasing platform performance by 400%.
• Architected and delivered the next-generation middleware platform for trading systems across London, New York, and Tokyo.
• Managed a 300% growth in infrastructure capacity over 3 years without service disruption.
• Increased resource fungibility across business units by leading a cross-training programme for over 100 employees.
• Led contingency and capacity management for Fixed Income market data distribution infrastructure.

A global enterprise software vendor of real-time integration and messaging middleware for large financial and telecom organizations. Leonardo started by leading pre-sales evaluations for top-tier financial and telco clients across EMEA. He was then promoted to manage the pre-sales and post-sales engineering team for the SmartSockets product, with responsibility for over $2 million in revenue.

• Managed a team of pre-sales and post-sales engineers for the SmartSockets product, owning over $2M in revenue.
• Led pre-sales evaluations for top-tier financial and telco clients across EMEA.
• Built proofs of concept to show how the platform fit each client’s systems.
• Presented solutions to business and technical stakeholders.
• Prepared responses to RFPs and RFIs.

A US software vendor of real-time messaging middleware (SmartSockets) used by financial institutions and telecom companies to move high-volume data between mission-critical systems. Leonardo worked as an Applications Engineer in pre-sales and professional services, helping clients evaluate and adopt the platform. He supported major financial accounts, including stock exchanges and investment banks, and the region he covered was the company’s most profitable for three quarters in a row.

• Specialised in pre-sales and professional services for financial and telco companies.
• Provided pre-sales support for the company's most profitable region for three quarters in a row.
• Worked on key financial accounts including Philadelphia Stock Exchange, CSFB, Bear Stearns, and Toronto Stock Exchange.