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AI Engineer (Data & Reporting)
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About the Role:
We are working with a leading global technology and consulting organisation that is looking to appoint an AI Engineer – Data & Reporting to help design, build and deploy scalable AI and machine learning solutions.
This is a hands-on technical role sitting at the intersection of data science, machine learning engineering, software engineering and business reporting. The successful candidate will work closely with business stakeholders, sales operations and technical data teams to develop AI-driven solutions that generate actionable insights and improve intelligent decision-making.
You will take ownership of AI and machine learning solutions from problem definition through to development, deployment, monitoring and impact measurement. The role will involve working with Generative AI, LLMs, RAG architectures, recommendation engines, forecasting models, intelligent summarisation and advanced analytics.
This opportunity would suit an AI Engineer, Machine Learning Engineer or Data Scientist with strong engineering capability and recent hands-on exposure to Generative AI and modern machine learning technologies.
Key Responsibilities:
- Design and develop production-grade AI and machine learning solutions across data and reporting platforms.
- Build recommendation engines, agentic AI frameworks, Retrieval-Augmented Generation solutions and intelligent summarisation capabilities.
- Deploy machine learning models into batch and real-time environments, ensuring scalability, reliability and performance.
- Engineer solutions using large language models and foundation models to support chatbots, semantic search, summarisation and reporting use cases.
- Design APIs, SDKs and microservices that integrate AI, RAG and machine learning capabilities into enterprise applications.
- Own the end-to-end AI/ML lifecycle, including problem definition, data exploration, model development, validation, deployment and monitoring.
- Develop forecasting models, segmentation strategies, optimisation algorithms and early warning systems.
- Collaborate with engineering, sales operations and business stakeholders to embed intelligent capabilities into reporting and analytics platforms.
- Lead technical decision-making around AI infrastructure, model governance, monitoring and safety controls.
- Conduct experimentation, statistical analysis and causal inference studies to evaluate business impact.
- Mentor team members and contribute to best practices across model governance, reproducibility and data quality.
- Keep up to date with emerging AI and machine learning technologies and identify opportunities for innovation.
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Skills & Experience:
- Proven experience in AI engineering, machine learning engineering, data science, MLOps, data engineering or software engineering.
- Recent hands-on experience with Generative AI, LLMs and advanced analytics.
- Strong Python and/or R programming experience.
- Experience using machine learning frameworks such as TensorFlow, PyTorch or scikit-learn.
- Experience with modern AI frameworks such as FastAPI, LangChain, LlamaIndex or similar technologies.
- Hands-on experience with LLM APIs, foundation models, embeddings, vector databases, RAG architectures or agentic AI systems.
- Strong understanding of software engineering best practice, including version control, CI/CD, containerisation, monitoring and deployment automation.
- Experience working with large-scale datasets using SQL, Spark or distributed processing platforms.
- Experience working with cloud-based infrastructure.
- Ability to translate business challenges into scalable AI and machine learning solutions.
- Strong communication and data visualisation skills, with the ability to explain complex technical concepts to technical and non-technical audiences.
- Experience collaborating with data engineers, software developers, business stakeholders and UX teams.
- Bachelor’s degree in Computer Science, Engineering, Statistics, Data Science or equivalent practical experience.
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Desirable Experience:
- Experience delivering AI-driven sales analytics, commercial insight or reporting solutions.
- Experience with revenue forecasting, sales planning or commercial operations analytics.
- Experience with anomaly detection, experimentation or causal inference.
- Familiarity with RabbitMQ, Redis, Valkey or event-driven architectures.
- Knowledge of vector databases, knowledge graphs and advanced data modelling approaches.
- Master’s degree or PhD in Computer Science, Engineering, Statistics, Data Science or a related quantitative discipline.
What's on Offer:
- Opportunity to work on modern AI, machine learning and Generative AI solutions.
- Exposure to LLMs, RAG, agentic AI, advanced analytics and scalable data platforms.
- Hybrid working from London.
- Opportunity to shape intelligent reporting and commercial insight solutions.
- Competitive salary and benefits package.
- Long-term career development within a global technology environment.
Apply:
If you are an AI Engineer, Machine Learning Engineer or Data Scientist with strong hands-on experience across Generative AI, LLMs, RAG, Python and scalable ML solutions, we would be keen to speak with you.
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