Machine Learning Quality Engineer

LSEG; Hyderabad; On-site; INR 1,500,000 - 2,100,000; Full time

Job summary

London Stock Exchange Group (LSEG) invites applications for a Senior Associate in the Corporate Engineering AI team in Hyderabad. The role focuses on defining evaluation frameworks, building automated test pipelines, and mitigating risks in agentic AI platforms used across the enterprise.

You will collaborate with ML Engineers to ensure governance, security, and audit readiness, contributing to scalable, safe AI capabilities in a regulated engineering environment.

Qualifications

• Experience with Python for test harnesses and automation.
• Familiarity with LLM evaluation frameworks or custom pipelines.
• Proficiency in designing test strategies for agentic systems.
• Understanding of governance, security, and audit requirements.
• Experience in regulated or highly governed engineering environments.
• Ability to collaborate with ML engineers and product teams.

Responsibilities

• Define evaluation frameworks for MCP tools and Skills.
• Build automated test pipelines for agentic behaviours.
• Evaluate and mitigate agentic failure modes (hallucination, tool misuse, latency).
• Produce testing evidence for PTB and PTO.
• Collaborate with ML Engineers to embed testability into MCP servers.
• Help shape long-term quality and governance for federated MCP contributions.

Skills

Python

LLM evaluation

Test automation

Agentic risk

Governance & security

Regulated environments

Job description

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.

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 Associate

London 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.

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.

LSEG offers a range of tailored benefits and support, including healthcare, retirement planning, paid volunteering days and wellbeing initiatives.