Machine Learning Quality Engineer
AI in this role
Corporate Engineering AI (CE AI) Team
The Corporate Engineering AI team is the central enablement and platform delivery function for LSEG’s internal agentic AI ecosystem. The team’s mission is to scale safe, high‑quality AI capabilities across the enterprise by providing shared platforms, patterns, governance, and delivery support.
CE AI owns and operates core AI platforms including LSEG AI Assist, the Question Answering Service (QAS), and the Internal MCP Gateway. Rather than delivering individual business use cases end‑to‑end, the team enables product engineering groups across LSEG to expose knowledge, data, and actions to AI agents in a consistent, governed, and repeatable way.
The team operates a Central MCP Delivery model: building critical MCP tools and services “for” product teams where required, while simultaneously defining standards, patterns, and platform capabilities that allow teams to progressively move towards self‑service contribution.
LSEG AI Assist / Internal MCP Programme of Work
This programme delivers an LSEG‑owned, production‑grade agentic AI platform with MCP as its extensibility layer.
The scope of work includes:
* Building and operating LSEG AI Assist, an in‑house agentic experience capable of reasoning, planning, and tool‑calling.
* Operating QAS, the enterprise RAG and search layer used to ground agent responses in approved data sources.
* Delivering a production Internal MCP Gateway providing discovery, security, policy enforcement, observability, and lifecycle management for MCP tools and Skills.
* Designing and building MCP servers and Skills that expose internal and vendor systems safely to agents.
* Establishing evaluation, quality control, and governance mechanisms so MCP tools and Skills can be promoted through PTB/PTO and operated with confidence at scale.
The programme follows a “build for” model today, with a strong emphasis on defining the future product and platform experience, patterns, and contribution pathways that will enable federated scale over time.
Quality Engineers – Responsibilities & Skills
Responsibilities
* Define and implement evaluation frameworks for MCP tools and Skills covering correctness, safety, and regression impact.
* Build and maintain automated test pipelines for agentic behaviours, including tool invocation and multi‑step workflows.
* Evaluate and mitigate agentic failure modes such as hallucination, tool misuse, invalid inputs, and latency amplification.
* Produce testing evidence required for Permit to Build (PTB) and Permit to Operate (PTO).
* Partner with ML Engineers to embed testability and evaluation hooks into MCP servers and Skills.
* Help define the long‑term quality and governance model for federated MCP contributions across LSEG.
Skills
* Strong Python experience for test harnesses and automation.
* Experience with LLM and RAG evaluation frameworks or custom evaluation pipelines.
* Test automation expertise covering unit, integration, and regression testing.
* Understanding of agentic system risks and failure modes.
* Ability to assess solutions against governance, security, and audit expectations.
* Experience working in regulated or highly governed engineering environments.
Career Stage:
Senior AssociateLondon Stock Exchange Group (LSEG) Information:
Join us and be part of a team that values innovation, quality, and continuous improvement. If you're ready to take your career to the next level and make a significant impact, we'd love to hear from you.
LSEG is a leading global financial markets infrastructure and data provider. Our purpose is driving financial stability, empowering economies and enabling customers to create sustainable growth.
Our purpose is the foundation on which our culture is built. Our values of Integrity, Partnership, Excellence and Change underpin our purpose and set the standard for everything we do, every day. They go to the heart of who we are and guide our decision making and everyday actions.
Working with us means that you will be part of a dynamic organisation of 25,000 people across 65 countries. However, we will value your individuality and enable you to bring your true self to work so you can help enrich our diverse workforce.
We are proud to be an equal opportunities employer. This means that we do not discriminate on the basis of anyone’s race, religion, colour, national origin, gender, sexual orientation, gender identity, gender expression, age, marital status, veteran status, pregnancy or disability, or any other basis protected under applicable law. Conforming with applicable law, we can reasonably accommodate applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs.
You will be part of a collaborative and creative culture where we encourage new ideas. We are committed to sustainability across our global business and we are proud to partner with our customers to help them meet their sustainability objectives. Our charity, the LSEG Foundation provides charitable grants to community groups that help people access economic opportunities and build a secure future with financial independence. Colleagues can get involved through fundraising and volunteering.
LSEG offers a range of tailored benefits and support, including healthcare, retirement planning, paid volunteering days and wellbeing initiatives.
Please take a moment to read this privacy notice carefully, as it describes what personal information London Stock Exchange Group (LSEG) (we) may hold about you, what it’s used for, and how it’s obtained, your rights and how to contact us as a data subject.
If you are submitting as a Recruitment Agency Partner, it is essential and your responsibility to ensure that candidates applying to LSEG are aware of this privacy notice.
How we rate this
Machine Learning Quality Engineer at LSEG rates 87 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.
Prepare for this job
A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.
Skills and AI tools this role asks for
Questions you could be asked
- How would you design a retrieval step so the model answers from real data instead of guessing?
- How do you decide when an AI agent can act on its own versus asking for approval first?
- How would you decide a model or AI system is ready to ship?
- Tell me about a time a model underperformed in production. How did you find out, and what did you change?
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- List these exact terms on your resume: RAG and AI Agents. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped — this role is judged on the AI system itself, not the tools around it.
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