At a Glance
- Tasks: Lead AI deployments, from discovery to production, solving real business challenges.
- Company: Join TP ICAP, a global leader in market infrastructure and innovative solutions.
- Benefits: Enjoy competitive salary, flexible working, and opportunities for professional growth.
- Other info: Inclusive culture that values diverse perspectives and encourages personal growth.
- Why this job: Make a real impact with cutting-edge AI technology in a dynamic environment.
- Qualifications: Experience in AI technologies, Python, and scalable solution design required.
The predicted salary is between 72000 - 88000 £ per year.
The TP ICAP Group is a world leading provider of market infrastructure. Our purpose is to provide clients with access to global financial and commodities markets, improving price discovery, liquidity, and distribution of data, through responsible and innovative solutions. Through our people and technology, we connect clients to superior liquidity and data solutions. The Group is home to a stable of premium brands. Collectively, TP ICAP is the largest interdealer broker in the world by revenue, the number one Energy & Commodities broker in the world, the world’s leading provider of OTC data, and an award winning all-to-all trading platform. Founded in London in 1866, the Group operates from more than 60 offices in 27 countries. We are 5,200 people strong. We work as one to achieve our vision of being the world’s most trusted, innovative, liquidity and data solutions specialist.
Role Overview: This is one of several newly created opportunities across our business functions, that will sit within our Group Technology function as an Associate Forward Deployed Engineer (AI) and be seconded out to various functions across the business including but not limited to Group Internal Audit, Operations and Human Resources. As the Associate Forward Deployed AI Engineer is a high-autonomy, high-impact role at the intersection of delivery and core platform development. You will embed directly with TP ICAP’s business divisions to lead end-to-end deployments of AI solutions. Owning discovery, technical scoping, system design, build, and production rollout. You will partner directly with domain teams to identify high-value AI opportunities, architect solutions tailored to real business problems and drive adoption from first prototype to stable production. Equally, you will serve as a critical feedback channel to TP ICAP’s central AI platform team, sharing field insights that shape product direction and model improvement. The role offers a unique opportunity to lead critical projects, shape engineering culture, and accelerate your career growth in the rapidly evolving field of generative AI.
Responsibilities:
- Own the full lifecycle of AI deployments within your assigned business division. Initial discovery and technical scoping through system design, build, and production rollout.
- Ensure solutions are technically sound, aligned to business outcomes, and delivered with the urgency and quality expected of a forward-deployed team.
- Embed directly with business stakeholders to understand their most pressing challenges.
- Translate complex domain requirements into well-defined technical solutions, operating as a trusted engineering partner rather than a distant service provider.
- Communicate progress, trade-offs, and outcomes clearly to leadership.
- Architect, build, and deploy cutting-edge AI applications powered by large language models and generative AI.
- Write and review production-grade code across frontend and backend systems, ensuring scalability, reliability, and strict data stewardship.
- Co-develop and enhance TP ICAP’s shared AI service platform in collaboration with the central AI & Innovation Lab.
- Feed field insights back to inform product roadmaps, identify where models succeed, and surface areas for improvement.
- Drive adoption of deployed solutions by measuring success through production usage, measurable workflow impact and evaluation-driven feedback.
- Present outcomes and strategic recommendations to leadership, demonstrating tangible business value.
Experience / Competences:
Essential:- Expertise in AI technologies, including Generative AI and Machine Learning.
- Hands-on experience working with Large Language Models (LLMs).
- Demonstrated proficiency in Python AI/ML frameworks with the ability to write and review production-grade code across the full stack.
- A proven track record architecting and designing scalable solutions that move from prototype to production.
- Experience managing technical priorities within an Agile environment, resolving dependencies and ensuring alignment across stakeholders and platform teams.
- Strong communication skills with the ability to present complex technical concepts to non-technical stakeholders and senior leadership, translating AI capabilities into business language.
- AWS experience including AI services such as Bedrock and the Serverless ecosystem.
- Proficiency in front-end technologies, particularly with React.
- Evidence of building intuitive, responsive user interfaces that integrate seamlessly with AI-driven back-end services.
- Expertise in back-end development, with experience in building and deploying scalable APIs and microservices to support AI solutions.
- Knowledge of OAuth (Okta) for implementing secure, scalable authentication and authorisation mechanisms in full-stack applications, ensuring data protection and privacy across AI solutions.
Location: UK - 135 Bishopsgate - London
Associate Forward Deployed Engineer (AI) in London employer: Liquidnet
Liquidnet is an exceptional employer located in the vibrant city of London, offering a dynamic work culture that fosters innovation and collaboration. Employees benefit from comprehensive professional development opportunities, competitive compensation, and a supportive environment that encourages growth within the electronic trading sector. With a focus on enhancing client relationships and driving revenue, Liquidnet provides a meaningful and rewarding career path for those passionate about trading and technology.
StudySmarter Expert Advice🤫
We think this is how you could land Associate Forward Deployed Engineer (AI) in London
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Liquidnet!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Associate Forward Deployed Engineer (AI) at Liquidnet.
✨Leverage Professional Networks
Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Liquidnet.
✨Apply Directly through Our Website
When you find a suitable opening like Associate Forward Deployed Engineer (AI) at Liquidnet, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace Associate Forward Deployed Engineer (AI) in London
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Liquidnet, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Liquidnet. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Liquidnet
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Liquidnet!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
