Applied AI Engineer
Summary
The Applied AI Engineer will leverage generative AI tools to enhance business analysis, documentation, coding, and research processes. The role requires a quantitative degree and at least two years of experience in data analytics or AI implementation.
Salary: £34,000 - 57,000 per year
Requirements:- Bachelors or Masters degree in Computer Science, Data Science, Engineering, Information Systems, Business Analytics, Economics, Mathematics, or a related technical or quantitative field.
- 2+ years of experience in data analytics, business analysis, technology enablement, AI implementation, automation, systems configuration, or a related role.
- Strong practical experience using generative AI tools to improve analysis, documentation, coding, research, workflow automation, or business productivity.
- Working knowledge of LLM concepts, including prompting, context windows, retrieval, hallucination risk, structured outputs, model selection, and evaluation tradeoffs.
- Familiarity with applied AI patterns such as RAG, embeddings, vector search, document extraction, tool calling, agentic workflows, and human-in-the-loop review.
- Strong programming and data skills, including Python, SQL, and tools/libraries used in agentic development like langgraph, langchain, Pydantic models, NumPy, FastAPI/MCP, etc.
- Ability to work with APIs, JSON, MCPs, Git or version-controlled artifacts, and lightweight automation or prototyping workflows.
- Excellent written and verbal communication skills, with the ability to translate business needs into technical requirements and explain AI concepts in plain language.
- Strong problem-solving skills, curiosity, attention to detail, and ability to work independently while collaborating across commercial, technology, and control functions.
- Understanding of responsible AI and software practices, including data sensitivity, access control, auditability, and appropriate escalation of higher-risk use cases.
- Proven ability to work effectively in a fast-paced, dynamic, and high-intensity environment with timely responsiveness and flexibility to work beyond normal business hours when required.
- Prior experience in commodities, energy, trading, logistics, asset operations, market analytics, or commercial decision-support workflows.
- Hands-on familiarity with enterprise AI tools such as Claude, ChatGPT/OpenAI, Gemini, Microsoft 365 Copilot, Cursor, or GitHub Copilot.
- Exposure to Snowflake, vector databases, knowledge-base configuration, and cloud platforms such as AWS or Azure.
- Portfolio examples showing practical AI use: an agent, workflow automation, prompt/context library, RAG prototype, document extraction workflow, evaluation framework, or AI-enabled business process improvement.
- Partner with traders, analysts, operators, technologists, and business stakeholders to identify workflows where AI can reduce manual effort, improve quality, or accelerate analysis.
- Configure and support approved AI tools and platform capabilities, including GenAI projects, agents, skills, knowledge bases, SQL resources, model presets, and MCP-enabled tools.
- Design and maintain high-quality AI context, including system instructions, prompt templates, examples, reference materials, retrieval sources, workflow guardrails, and output formats.
- Support RAG and document-intelligence workflows, including document ingestion, chunking, metadata design, retrieval quality, structured extraction, and validation with subject-matter experts.
- Evaluate AI outputs for accuracy, groundedness, completeness, formatting, usability, and business value; use feedback and test cases to improve configurations over time.
- Create reusable playbooks, templates, demos, and reference materials that help technology and commercial teams use AI safely and effectively.
- Communicate AI capabilities, limitations, risks, and recommended usage patterns clearly to both technical and non-technical stakeholders.
- Stay current on practical advancements in applied AI, context engineering, enterprise copilots, agentic workflows, RAG, and AI evaluation methods.
- AI
- AWS
- Azure
- ChatGPT
- Cloud
- Copilot
- Cursor
- FastAPI
- Git
- GitHub
- Support
- JSON
- LLM
- MCP
- Microsoft 365
- Python
- RAG
- SQL
- Snowflake
- Windows
- numpy
- Office 365
More:
We are seeking a talented and detail-oriented Applied AI Engineer to join our Global Data Science team and help internal technology and commercial teams adopt CCIs approved AI tooling effectively. In this full-time role based in London, UK, we offer competitive comprehensive medical, dental, retirement and life insurance benefits, employee assistance and wellness programs, parental and family leave policies, two annual volunteer days through our Charity Committee program, charitable contribution matching, tuition assistance and reimbursement, quarterly Innovation & Collaboration Awards, an employee discount program with access to fitness facilities, competitive paid time off, and continued learning opportunities. We also support our employees, their families, and local communities through our community programs.
last updated 35 week of 2026