18 days ago
London, United KingdomStaff+
Responsibilities
- Lead consultancy engagements end-to-end from opportunity shaping and work-winning through delivery governance and team leadership.
- Deliver production-grade AI/ML and software solutions embedded within client teams and business processes.
- Design and build agentic AI and LLM systems using RAG, MCP servers, prompt engineering, major LLM SDKs, and agent frameworks.
- Execute machine learning lifecycles including feature engineering, model training, evaluation, deployment, MLOps, monitoring, and drift detection.
- Develop Python services, frontend applications, cloud architectures, and data storage strategies across relational, NoSQL, graph, and caching systems.
- Advise clients and lead teams on operationalisation, reliability, governance, security-conscious development, testing, and release management.
Requirements
- 1–5 years of experience in technology consulting, software engineering, or AI/ML.
- SME-level depth in at least one of agentic AI/LLM engineering, machine learning engineering, or software engineering, with strong architecture and design capability.
- Expertise in relevant AI/ML, cloud, software, data, and architecture technologies, including production delivery at scale.
- Clear and confident communication skills for technical and non-technical audiences and credible client representation.
- Master’s degree in Computer Science, Engineering, Mathematics, Data Science, or a related discipline, or equivalent depth through relevant professional certifications.
- Prior experience as a forward-deployed or embedded engineer in a client environment.
- Exposure to regulated industries such as energy, financial services, or the public sector.
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