AI Engineer Consultant

• Advance and improve existing AI prototypes and engineering pipelines.
• Develop maintainable AI and machine learning components using Microsoft Azure services.
• Enhance search orchestration processes, manage evidence tracking, ensure provenance, and improve quality control and assessment workflows.
• Implement persistent data storage, version control, and incremental data processing.
• Create or prototype user interfaces such as dashboards, Microsoft 365 agents, or lightweight web apps.
• Package AI solutions following software engineering, security, and deployment best practices.
• Produce technical and architecture documentation including integration patterns, data flows, security measures, assumptions, risks, deployment needs, and operational responsibilities.
• Develop reusable solution templates, blueprints, diagrams, checklists, and handover materials.
• Support enterprise system integrations like Salesforce and ServiceNow.
• Design and evaluate text classification methods, comparing large language models, hybrid and minimal LLM approaches.
• Assess models based on accuracy, cost, latency, explainability, robustness, and maintainability.
• Plan reproducible experiments and document findings and recommendations.
• Build or integrate AI solutions using APIs, handling both structured and unstructured data.
• Support workflows involving grounded search, retrieval-augmented generation, evidence management, and agentic processes.
• Participate in code and design reviews and technical demonstrations.
• Maintain source control, track work progress, and document technical decisions.
• Produce reusable code, deployment guidance, and documentation.
• Conduct knowledge transfer and prepare handover materials.

• Degree in Computer Science, Data Science, Artificial Intelligence, Engineering or a related field, or equivalent professional experience.
• Strong analytical and problem-solving skills.
• Fluent written and spoken English.
• Ability to explain technical concepts clearly to both technical and non-technical audiences.
• Hands-on experience with Python programming.
• Experience developing AI, machine learning, and generative AI solutions.
• Knowledge of software engineering practices including modular development, testing, and code reviews.
• Experience with Git/source control and continuous integration/continuous deployment (CI/CD).
• Familiarity with Microsoft Azure and Azure AI services including Microsoft Foundry.
• Experience with Azure Databricks, Azure SQL Database or SQL Server, and Azure DevOps.
• Skills in text classification and machine learning experimentation.
• Ability to evaluate models for accuracy, cost, performance, and optimisation.
• Experience with API-based enterprise integrations.
• Experience working with structured and unstructured data.
• Ability to produce technical architecture and solution documentation.
• Understanding of security, access control, data protection, and responsible AI principles.
• Preferred experience with Microsoft Copilot Studio, Microsoft Power Platform, retrieval-augmented generation and grounded web search, evidence provenance, knowledge engineering, agentic workflows, and model orchestration.
• Experience comparing large language models, smaller models, traditional machine learning, rules-based, and hybrid approaches is preferred.
• Experience in global health, international development, public sector, or regulated environments is a plus.
• Relevant Microsoft certifications in Azure AI, Data, Cloud, or Power Platform are highly desirable.

Apply through the employer's official contact by submitting your application before the closing date, which has not been published.