At a Glance
- Tasks: Design and develop cutting-edge AI products for financial markets.
- Company: Join a global leader in financial markets infrastructure.
- Benefits: Enjoy healthcare, retirement planning, and paid volunteering days.
- Other info: Collaborative environment with opportunities for continuous learning and growth.
- Why this job: Make a real impact with innovative AI solutions in finance.
- Qualifications: Extensive software engineering experience and AI system development.
The predicted salary is between 72000 - 88000 £ per year.
Описание
LSEG is a global financial markets infrastructure and data provider.
It enables businesses and economies to fund innovation, manage risk and create jobs through trusted financial market infrastructure services and an open-access model.
- Задачи
- Design, develop and deploy enterprise-grade AI products and services;
- Build agentic AI workflows, retrieval-augmented generation solutions and intelligent automation capabilities;
- Deliver scalable integrations with LLMs, MCP services, vector databases and enterprise platforms;
- Develop reusable AI frameworks, accelerators and engineering standards;
- Lead technical implementation across multiple AI initiatives;
- Define solution architecture and engineering patterns for AI products;
- Build robust APIs, orchestration services and automation pipelines;
- Drive security, scalability, resilience and observability requirements;
- Partner with Product Managers, Data Scientists and Engineering teams to deliver AI solutions from concept through production;
- Support the development of AI platforms that enable wider engineering adoption;
- Establish monitoring, evaluation and governance processes for AI systems;
- Improve the reliability and performance of deployed AI capabilities;
- Act as a technical leader across AI initiatives;
- Mentor engineers and contribute to the development of AI engineering capability;
- Evaluate emerging AI technologies and identify opportunities to accelerate delivery;
- Provide technical direction on architecture, tooling and engineering practices;
- Translate business challenges into scalable AI solutions;
- Define measurable KPIs and success measures;
- Ensure solutions drive productivity improvements, operational resilience and customer value;
- Partner with stakeholders across Engineering, Operations and Product organisations.
- Требования
- Extensive software engineering experience delivering production-scale solutions;
- Experience building AI or machine learning systems in enterprise environments;
- Demonstrated experience moving AI solutions from proof of concept into production;
- Strong understanding of software architecture, engineering standards and operational practices;
- Ability to influence technical direction across teams without formal management responsibility;
- Strong ownership mindset and delivery focus;
- Ability to solve ambiguous and highly complex problems;
- Excellent stakeholder engagement and communication skills;
- Collaborative leadership through influence;
- Commitment to responsible and ethical AI development;
- Passion for continuous learning and innovation;
- Nice to have: Experience within Financial Services or highly regulated environments, knowledge of Service Reliability Engineering principles, experience developing AI-powered operational tooling, experience building internal AI platforms or developer enablement capabilities, familiarity with Microsoft AI ecosystem, Copilot technologies and Azure AI services.
- Условия
London, England, United Kingdom; Healthcare, retirement planning, paid volunteering days and wellbeing initiatives.
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ai engineer in financial markets infrastructure employer: Enfint
As a leading innovator in AI products for major publishers, our company offers an inspiring work environment where creativity and technology intersect. We prioritise employee growth through continuous learning opportunities and foster a collaborative culture that values diverse perspectives. Located in a vibrant city, we provide competitive salaries, relocation support, and the chance to make a real impact in the media landscape.
StudySmarter Expert Advice🤫
We think this is how you could land ai engineer in financial markets infrastructure
✨Join Local Tech Meetups
Get out there and mingle with fellow developers by joining local tech meetups. It’s a fantastic way to meet people who might be working at Enfint or know someone who does. Plus, you can pick up some trendy tech skills and trends while you're at it!
✨Contribute to Open Source Projects
Show off your coding chops by jumping into open-source projects. Not only does this give you practical experience, but it also gets you noticed in the dev community. You'll create a killer portfolio that speaks volumes about your skills to Enfint.
✨Tap into Online Developer Communities
Don’t underestimate the power of online developer communities like GitHub, Stack Overflow, and even Reddit. Participate in discussions, share your projects, and build your visibility. We can often find opportunities through these channels that can lead to a full-time gig at companies like Enfint.
✨Explore Job Boards Specifically for Tech Roles
Keep your eyes peeled on job boards that focus on tech roles. Sites like TechCareers or Stack Overflow Jobs can often have listings for companies like Enfint that might not show up on broader job sites. Make it a habit to check these regularly, and don’t hesitate to apply directly through our website!
We think you need these skills to ace ai engineer in financial markets infrastructure
Some tips for your application 🫡
Show off your coding skills:When applying for a software engineering role, it's super important to showcase your coding skills. Make sure your CV includes your tech stack, any relevant programming languages you’re comfortable with, and examples of projects you've worked on. If you have a GitHub profile, link it up! We love to see code in action.
Tailor your portfolio:For a full-time role, we’d expect to see some solid examples of your work in your portfolio. Make sure to include at least two or three projects that highlight your problem-solving skills and your ability to work with different technologies. Focus on the projects that are most relevant to the position at Enfint.
Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at Enfint and how your skills align with the role. Show us your passion for software development. We dig enthusiastic candidates who understand the value of collaboration and continuous learning!
Be clear and concise:When it comes to writing your CV and cover letter, clarity is key. Avoid jargon that could confuse us and stick to simple, direct language. Highlight your achievements with quantifiable results where possible, and keep everything easy to read. A well-organised application goes a long way!
How to prepare for a job interview at Enfint
✨Brush Up on Your Coding Skills
For a full-time software engineering role, it's crucial that we stay sharp with our coding abilities. Expect technical questions that might involve solving problems on the spot or discussing algorithms. Practise on platforms like LeetCode or HackerRank to get comfortable with the types of questions that often come up.
✨Know Your Tools and Frameworks
Make sure we’re well-acquainted with the tools and technologies listed in the job description. Familiarise ourselves with any specific frameworks or programming languages mentioned. If Enfint uses React or Node.js, for instance, be ready to discuss how we’ve used them in previous projects or coursework.
✨Showcase Your Projects
Bring along a portfolio that highlights our best work. This could be code samples, GitHub repositories, or any side projects we’ve built. Make sure we can talk through our thought process for each project, especially the challenges we faced and how we solved them—this shows our problem-solving skills in action.
✨Prepare for Behavioural Questions
While technical skills are key, full-time positions also require cultural fit. Be ready to discuss our previous experiences and how we handle teamwork, conflict, and deadlines. Brush up on the STAR method—Situation, Task, Action, Result—to clearly articulate our past experiences when discussing how we've contributed to a team.
