Louise Kirkham - Senior AI Engineer

Louise Kirkham

Senior AI Engineer | MLOps Practitioner | Solution Architect

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About Me

Senior AI Engineer with extensive experience developing enterprise ML solutions across diverse UK and global organisations in a range of sectors. I specialise in MLOps, GenAI and responsible AI development, translating complex client requirements into scalable solutions that deliver measurable business value. I take a pragmatic, impact-focused approach that prioritises simplicity while delivering robust solutions and I'm committed to responsible AI by design.

Core Skills

MLOps & Platform Engineering

CI/CD for ML, model governance, automated retraining, cloud deployment, monitoring and observability, feature stores, model versioning

GenAI & LLM Systems

RAG architecture, LLMOps, agentic workflows, responsible AI frameworks, fine-tuning, prompt engineering, multi-modal AI systems

Solution Architecture & Strategy

Enterprise AI platform design, multi-cloud deployment, technical due diligence

Client Engagement

Technical pre-sales, solution design, stakeholder management

Leadership & Development

Line management, team mentoring, L&D initiatives, ethics working groups, secure deployment best practices

Technology Stack

Python
Microsoft Azure
Azure DevOps
GCP
Docker
Kubernetes
Databricks
Snowflake
LangChain
OpenAI
dbt
Gemini
MLflow
Terraform
Spark
TensorFlow
PyTorch
FastAPI
Chroma
LangSmith

Professional Experience

Senior Consultant AI Engineer

Datasparq
February 2023 - Present

Strategic Client Leadership & Revenue Generation

  • Architect complex enterprise solutions, including multiple global consumer healthcare projects such as NGQRM Phase 3 integration connecting 7 disparate source systems across global operations
  • Support technical pre-sales for major clients including supply chain, consumer healthcare, facilities management and private equity firms
  • Lead MLOps Assessments such as for major insurance group across 4 business units, engaging C-suite stakeholders (CDAO, CTO)

Key Project Deliveries:

Leading Transactional Insurance Underwriter: SPA Red Flag Assistant - GenAI Document Intelligence

Challenge: Leading transactional insurance underwriter needed to accelerate Sale & Purchase Agreement reviews (manual process took hours per document)
Solution: Built LLM-powered system fine-tuned with client's underwriting principles for intelligent flagging of problematic language with explainable AI rationales
Impact: 92% accuracy, 6+ hours saved per document, ~3 FTE productivity enhancement
Technologies: Fine-tuned LLMs, SharePoint integration, custom prompt engineering, explainable AI frameworks

International Manufacturing Company: Smart Inventory Optimisation

Challenge: International manufacturer losing revenue through inaccurate demand forecasting across global SKU portfolio
Solution: Designed ensemble forecasting system with dynamic model selection, integrated and scalable Azure DevOps/Snowflake/dbt pipeline
Impact: 10x ROI in under 2 years ($633k annualised revenue uplift), doubled forecasting accuracy, +110 hours monthly labour savings
Technologies: Azure DevOps, Snowflake, dbt, Python, ensemble ML forecasting methods

Global Consumer Healthcare Brand: GenAI Content Intelligence Suite

Challenge: Global consumer healthcare organisation needed automated regulatory compliance and inclusivity screening for marketing content
Solution: Multi-modal GenAI system combining LLM-powered content analysis, computer vision for demographic assessment and regulatory knowledge integration
Impact: 60% reduction in content review cycle time, increased brand safety compliance consistency, enabled higher campaign throughput
Technologies: Azure OpenAI, Computer Vision APIs, RAG architecture, custom prompt engineering

Additional Achievements:

  • Generated follow-on client engagements through technical excellence
  • Led internal GenAI working group, defining secure LLM deployment best practices
  • Line managed mid level engineers with focus on career development and technical growth
  • Led Learning and Development initiatives for the Engineering team
  • Co-led internal ethics working group, implementing anonymous concern reporting and ethical AI frameworks

Consultant AI Engineer

Datasparq
April 2022 - February 2023

Established strong technical partnerships with key enterprise clients, demonstrating value through proof-of-concept deliveries and stakeholder engagement. Rapidly developed expertise in GenAI technologies, MLOps practices and cloud-native deployment patterns while supporting major enterprise engagements and foundational MLOps assessment frameworks.

Senior Data Scientist

Royal Mail Group
July 2018 - April 2022
  • HEADS Automated Diversion System: Led end-to-end development of ML-powered route optimisation serving national logistics network. Reduced network losses to 10-year low, supporting £150M annual regulatory compliance target.
  • Cloud Migration & CI/CD Implementation: Redeployed on-premise data science solutions to the cloud and developed new CI/CD processes. Achieved faster delivery by the whole data science team, 50% cost reduction and improved stability and reliability.
  • Additional Impact: Built production models for revenue prediction, recommender systems and demand forecasting. Established MLOps practices across data science organisation.

Senior Research Scientist

Defence Science and Technology Laboratory (DSTL)
November 2012 - July 2018
  • Providing scientific expertise to support research and development projects within the Sensing and Detection group of the Counter Terrorism and Security division
  • Experimental design and evaluation of detection and diagnostic technology for military and security applications
  • Lead an experimental trial team to deliver cutting edge research including laser-plasma acceleration at a world-class high-power laser facility (CLF, SLAC). Associated publication: Response of nuclear track detector CR-39 to low energy muons H S P Thomas et al 2021 Plasma Phys. Control. Fusion 63 124001

Education & Certifications

MSc Radio Wave Imaging and Sensing

University of Manchester
2011-2012 (Distinction)
Dissertation: Characterisation and Calibration of a Large Aperture (1.6 m) ka-band Indoor Passive Millimetre Wave Security Screening Imager Proc. SPIE 8544, Millimetre Wave and Terahertz Sensors and Technology V, 854408 (26 October 2012)

MPhys Physics with Astrophysics

University of York
2004-2008 (2:1)

Certified Microsoft Azure ML Engineer Associate

Microsoft
Current