AI Engineer

Role: AI Engineer Location: London, UK (Hybrid) Type: Contract Position Please find below JD: Role Title: AI Engineer Minimum years of experience: 5+years with experience in generating sales insights and analytics using AI Job Description: - Design and build production-grade machine learning systems across the sales data platform, including building MCP servers, recommendation systems, agentic summarisation frameworks, and RAG pipelines at scale. - Deploy models into batch and real-time environments, ensuring scalability, reliability and performance - Engineer solutions using LLMs and foundation models to build applications such as chatbots, semantic search engines, and summary generation tools for a data reporting platform. - Design modular APIs, SDKs, and micro-services to integrate LLMs, RAG and traditional ML models into existing reporting solutions. - Own the end-to-end AI/ML lifecycle: problem definition, data exploration, model development, validation, deployment, and monitoring. - Develop forecasting models, segmentation approaches, and optimisation algorithms to drive sales strategy, and build early warning systems to identify risks and opportunities. - Drive interoperability with existing ML systems and support downstream applications such as dashboards, web tools, and chat interfaces. - Partner closely with engineering, sales ops, and business stakeholders to embed context-aware intelligence into decision-making tools and processes. - Lead technical decision-making on infrastructure, embedding safety mechanisms such as grounding checks and model monitoring. - Conduct experiments and causal analyses to evaluate the impact of business initiatives, and communicate findings clearly to technical and executive audiences. - Contribute to hiring, mentoring, and engineering best practices in model governance, reproducibility, and data quality. - Champion innovation by staying abreast of the latest advancements in AI/ML and actively seeking opportunities to apply new tools and techniques. Minimum Qualifications - Proven years of experience in MLOps, data engineering, or software development, with a recent focus on GenAI, LLMs, and advanced analytics. - Understanding of software engineering practices such as version control, CI/CD containerisation and monitoring, particularly within ML or MLOps context. - Proficiency in Python and/or R, with experience in ML libraries (scikit-learn, TensorFlow, PyTorch) and frameworks such as FastAPI, LangChain, or similar. - Hands-on experience with LLM APIs, foundation models, embeddings, vector databases, RAG workflows, and agentic AI systems including MCP. - Experience with large-scale datasets using SQL, distributed data platforms (e.g., Spark), and cloud-native infrastructure (e.g., AWS, GCP, or on-prem hybrid). - Strong data visualisation and communication skills, with the ability to explain complex models to both technical and non-technical audiences. - Ability to translate ambiguous business problems into structured AI/ML solutions, and to manage multiple projects independently in a fast-paced environment. - Prior experience collaborating with cross-functional teams including data engineers, developers, and UI/UX designers. - B.S. Degree in Computer Science, Engineering, Statistics, Data Science, or equivalent work experience. Preferred Qualifications - Past experience in generating sales insights and analytics using AI. - Strong experience translating business questions into AI/ML solutions and communicating results to senior leaders and diverse audiences. - Experience in revenue forecasting, or commercial operations. - Proven experience with GenAI frameworks (LangChain, LlamaIndex, etc.), anomaly detection, and causal inference models. - Familiarity with distributed systems technologies such as RabbitMQ, Redis, and Valkey, and with vector knowledge graph data modelling. - Advanced Degree (MS or Ph.D.) in Computer Science, Electrical Engineering, Statistics, Data Science, or a similar quantitative field.