Requirements
Candidates must be currently enrolled in an undergraduate degree program with hands-on experience in AI agents, LLMs, or workflow automation. Proficiency in Python or JavaScript, along with knowledge of APIs and CRM systems, is required for this role.
Job Description
As an AI Agent Developer Intern at CMC Markets, you will support the development of CMC Funded, a new education-led funded trading proposition. This is a hands-on, part-time opportunity for a current undergraduate student with strong practical experience in AI agents and workflow automation to contribute to a real project in a regulated fintech environment.
Working with the CMC Funded Project Lead and colleagues across Product, Client Service, Operations, Technology, Data, Compliance, Risk and Marketing, you will design, build, test and monitor AI-enabled customer support, customer relationship management (CRM) and operational workflows.
Your mission: help create secure, reliable and measurable AI solutions that improve customer onboarding, education, support and operational visibility. Customer-facing AI outputs, production changes and any activity with regulatory or trading implications will remain subject to approved controls and human oversight.
Key responsibilities
Design, build and improve AI agents and workflow automations for customer enquiries, onboarding, educational support, account and process guidance, case and lead management, CRM updates and internal operations.
Configure and maintain prompts, approved knowledge sources, retrieval-augmented generation (RAG), tool use, conversation routing, state management, guardrails and human escalation paths.
Develop and maintain integrations between AI and automation platforms, Intercom, CRM, helpdesk, data sources and analytics tools using REST APIs, webhooks and other approved methods.
Support an AI-enabled customer journey across Intercom and other approved communication or community channels, including WhatsApp, Meta, Discord or Telegram where authorised.
Improve CRM data quality, tagging, segmentation and lifecycle automation so customer interactions are complete, traceable and actionable.
Create dashboards, alerts and management information to monitor customer demand, service levels, AI agent performance, operational exceptions and customer journey outcomes.
Plan and run structured testing for accuracy, appropriateness, latency, reliability, security, escalation behaviour and customer experience; investigate issues and implement agreed improvements.
Apply secure development and responsible AI principles, including data minimisation, confidentiality, auditability, transparency, access control and appropriate human review.
Use practical knowledge of prop trading and funded trader journeys to translate customer and operational needs into product requirements, without providing personal investment advice or independently making trading, risk, compliance or client eligibility decisions.
Work with Product, Client Service, Operations, Technology, Data, Compliance, Legal, Risk, Data Protection, Information Security and Marketing stakeholders to deliver joined-up solutions.
Maintain clear technical and operational documentation, including solution designs, configurations, data flows, test evidence, change records, incident notes and runbooks.
Present prototypes, demonstrations, progress, risks and recommendations, and manage assigned work within agreed sprint and project priorities.
Requirements
Current enrolment in an undergraduate degree, ideally in computer science, AI, software engineering, data, fintech, finance or a related discipline.
Demonstrable hands-on experience building AI agents, large language model (LLM) applications or workflow automations for practical use cases through employment, projects or portfolio work.
Working knowledge of Python and/or JavaScript or TypeScript, REST APIs, webhooks, JSON, Git and database fundamentals.
Practical experience with prompt engineering, knowledge bases or RAG, tool calling, agent orchestration, testing, evaluation and monitoring.
Experience with CRM, helpdesk, customer support or lifecycle workflows; experience with Intercom or a comparable platform is preferred.
Practical understanding of prop trading, funded trader evaluation journeys and common customer or operational use cases.
Strong analytical, problem-solving, documentation and communication skills, with the ability to take ownership of defined tasks and escalate appropriately.
A responsible approach to data handling, privacy, information security, model limitations and customer-facing communications.
Availability to work 20 hours per week from the London office alongside academic commitments, subject to applicable UK right-to-work and immigration conditions.
Additional experience that would be advantageous
Experience with LangGraph, n8n, Make, Zapier or comparable agent orchestration and automation tools.
Experience with SQL, dashboards, analytics, cloud services, logging or observability tools.
Experience in financial services, fintech, a regulated environment, customer operations or an early-stage product team.
Experience integrating messaging or community platforms and using performance data to improve automated customer journeys.