Professional summary

AI & Data Engineer

AI Engineer with more than ten years in data engineering and analytics, now focused on building applied AI systems that hold up outside a demo. My work covers the full route from problem framing through model and prompt design, API integration, deployment and ongoing evaluation. I build AI features that sit inside real business systems rather than beside them, which means treating data flow, storage and monitoring as part of the AI work rather than someone else’s problem.

The data engineering background is the reason the AI work is reliable. Pipelines, quality control and governance are familiar ground, so the data feeding a model is something I can own end to end. Over the past two years I have used Claude Pro heavily as a development partner to design and ship SaaS products, MVPs and CMS platforms, moving from initial concept to working software much faster than a traditional build cycle allows. I hold an MSc in Big Data Analytics with Distinction and I am currently working through the Microsoft Learn career path for AI engineers.

Core skills

Applied AI and LLM engineering

• Prompt architecture, system instruction design and iterative output evaluation
• Retrieval-Augmented Generation (RAG) using LangChain and LlamaIndex
• LLM API integration: OpenAI, Anthropic Claude, Ollama, OpenRouter
• Model Context Protocol (MCP) server development and tool exposure
• Model benchmarking and comparative evaluation across hosted and open-source models
• Agentic and multi-step workflow design with human review built into the loop

Machine learning and data science

• Machine learning development lifecycle, from data preparation through to deployment and monitoring
• Natural language processing and document extraction use cases
• Feature preparation, validation and quality control for model inputs
• Statistical analysis and applied research methods

Engineering and platforms

• Python (pandas, requests, scripting, automation, API clients)
• SQL across reporting, warehouse and analytical workloads
• Azure Data Factory, Azure SQL Database, exposure to Microsoft Fabric
• Azure AI Foundry (developing experience, currently in active use)
• AWS: S3, EC2, Lambda, IAM
• Databricks: PySpark, Spark SQL, Delta Lake, Unity Catalog
• Power BI semantic modelling, DAX, Row-Level Security
• Git and GitHub, CI/CD concepts, technical documentation

Professional experience

AI & Data Engineer (Freelance), Binary Intelligence Limited, UK

Mar 2024 to present. Independent AI engineering practice covering LLM application development, prompt systems and AI-assisted product delivery for small businesses and startup clients.

• Design and build AI solutions that integrate with existing business systems, so that AI features extend what a client already runs instead of sitting in a separate tool nobody opens.
• Manage the data flow and infrastructure behind each deployment, covering ingestion, storage, retrieval and access control, which keeps model behaviour predictable once real data arrives.
• Use Claude Pro as a core development partner to design and develop SaaS products, MVPs and CMS projects, taking work from concept and architecture through to working, deployed software.
• Built a Python framework for systematic prompt testing across multiple LLM APIs, scoring outputs against defined quality criteria and logging results run by run for objective comparison.
• Benchmark models available through OpenRouter and Ollama against cost, latency and output quality, then match the model to the workload rather than defaulting to the best-known name.
• Deliver an ongoing healthcare AI project built on Alibaba’s Qwen model, working through data sensitivity, evaluation criteria and output reliability with the client.
• Test, deploy and maintain live AI systems, monitoring performance after release and retuning prompts, retrieval logic and configuration as usage patterns change.
• Track developments across the AI field and recommend improvements to existing client systems and workflows where a newer approach genuinely earns its place.

Data Infrastructure Analyst, Greenocean Petroleum Limited

Mar 2013 to Jan 2023

• Held end-to-end responsibility for enterprise reporting infrastructure across a ten-year tenure, managing the datasets and SQL queries used for performance monitoring throughout the organisation.
• Designed and maintained automated ETL and ELT pipelines in Python and SQL, integrating data from multiple business systems for operational and analytical use.
• Used pandas extensively for data manipulation, cleaning, transformation and validation, alongside complex SQL covering joins, aggregations and window functions.
• Wrote Python automation scripts for routine processing, which freed up meaningful time for more complex analytical work.
• Worked directly with operational teams to define KPIs, acting as the technical bridge between source systems and business reporting.

Data Analyst & Web Developer, Social Action (NGO), saction.org

Mar 2010 to Mar 2013

• Supported internal data systems and reporting tools, and built web-based tools for internal projects.
• Ensured data integrity across multiple input sources.

Education

MSc Big Data Analytics (Distinction), University of Derby, UK, 2023 to 2024.
Coursework covered machine learning and the model development process, distributed systems, big data processing with Spark, cloud analytics platforms and applied statistical programming.

B.Tech Computer Science, Federal University of Technology, Owerri, Nigeria, 2004 to 2010.

Certifications and professional development

Completed

• Generative AI Fundamentals, Databricks Academy: core generative AI concepts and practical business application.
• Analytics Fundamentals, Databricks Academy: unified semantics, AI/BI dashboards and lakehouse analytics.
• Azure Platform Architect, Databricks Academy platform administration, networking and security on Microsoft Azure.
• AWS Platform Architect, Databricks Academy: deployment, security and cloud integration on AWS.

In progress: Microsoft Learn career path for AI engineers

• Working through the self-paced Microsoft Learn plan for AI engineers, covering planning and management of an Azure AI solution, generative AI with Azure OpenAI and Azure AI Foundry, agentic solutions, natural language and speech, computer vision, and knowledge mining with Azure AI Search.
• Preparing for Exam AI-102, Microsoft Certified: Azure AI Engineer Associate, including the official practice assessment.

Selected projects

Odili MCP. A working Model Context Protocol plugin that connects a WordPress installation to Claude, letting site content and site operations be accessed as callable tools through an authenticated endpoint. A standalone version was also built in PHP and MySQL for use outside WordPress.

LLM Prompt Testing Framework. Python framework for running prompt variations across multiple LLM APIs, scoring responses against defined criteria and logging every run. It turned prompt iteration from guesswork into something measurable.

AI Workflow Automation for Small Businesses. Identified repetitive tasks suitable for automation with freelance clients, then built prompt-driven workflows for content drafting, document extraction and customer query handling. Every workflow keeps a human review step.

Additional information

• Eligible to work in the United Kingdom, available for remote, hybrid or on-site roles anywhere in the UK.
• Comfortable working across multidisciplinary teams, including data scientists, software developers, product managers and business stakeholders.
• Strong written communication, covering technical documentation, client-facing summaries and internal guidelines.
• Active interest in AI safety, responsible deployment and the practical limits of current LLM technology.

References and further details are available on request. Send me an email for more information.

vincentwap@gmail.com | vincentwap.co.uk | linkedin.com/in/vincentwap | github.com/vincentwap