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.