At a Glance
- Tasks: Design and develop cutting-edge AI solutions for Funds Transfer Pricing and Financial Hedging.
- Company: Join a leading financial services firm at the forefront of AI innovation.
- Benefits: Competitive salary, flexible working options, and opportunities for professional growth.
- Other info: Be part of a dynamic team with mentorship opportunities and a focus on engineering excellence.
- Why this job: Make a real impact by creating sophisticated AI agents that transform business processes.
- Qualifications: Experience in software development, Python, SQL, and multi-agent systems required.
The predicted salary is between 80100 - 97900 £ per year.
We are building the most consequential AI solutions in Funds Transfer Pricing and Financial Hedging platforms, and we are looking for a Senior AI Engineer to design & develop Agentic AI solutions for these domains. The ideal candidate is a visionary engineer, passionate about architecting and building sophisticated AI agents from concept to production. In this position, you will be responsible for creating agentic solutions that automate complex workflows, enhance critical decision-making, and deliver scalable, cutting-edge technology at a global scale.
Responsibilities
- Advanced Agent and Model Development
- Design and orchestrate complex multi-agent systems where autonomous agents collaborate, coordinate, negotiate, and delegate tasks to solve business problems that exceed the capabilities of a single agent.
- Design and implement advanced planning and reasoning capabilities using techniques such as knowledge graphs for relationship-aware reasoning, rule-based and symbolic reasoning for deterministic business decisions, and planning/search algorithms to execute complex multi-step workflows reliably and efficiently.
- Develop resilient and adaptive agent architectures with mechanisms for feedback-driven improvement, error recovery, self-correction, and dynamic replanning to enhance reliability, accuracy, and task completion rates.
- Integrate large language models (LLMs), predictive models, and reasoning frameworks to expand agent capabilities, improve decision quality, and support complex business workflows.
- Design and optimize Retrieval-Augmented Generation (RAG) architectures, including embedding strategies, vector databases, retrieval pipelines, reranking, and context management to maximize response accuracy and relevance.
- Design and develop APIs, tools, and microservices that enable seamless integration of AI capabilities with enterprise applications, databases, and business platforms.
- Performance and Optimization
- Optimize AI systems for low latency and high throughput.
- Implement advanced techniques such as response streaming and caching, while ensuring cost-effectiveness through strategic model selection and rigorous token usage optimization.
- Technical Leadership and Strategy
- AI Research and Strategy: Act as a subject matter expert, driving the technical strategy for AI within the Funds Transfer Pricing and Financial Hedging domains by staying abreast of state-of-the-art research and identifying opportunities for innovation.
- Mentorship and Technical Guidance: Mentor junior engineers on AI best practices and provide technical leadership across multiple project teams, fostering a culture of engineering excellence.
Required Qualifications & Skills
- Professional experience in software development and system design.
- Proficiency in Python and SQL, with experience in production-quality Agentic AI development; applied experience with frameworks like LangChain, LlamaIndex, or equivalents.
- A proven track record of architecting multi-agent systems using frameworks like Google ADK, LangGraph, AutoGen or CrewAI. This includes hands-on experience with planning/reasoning, memory systems, MCP and Vector DBs.
- Practical knowledge of LLMs and their application within agentic architectures, including API design and integration for AI services.
- Demonstrated mastery of Prompt and Context Engineering, including the ability to structure and compress information for optimal model performance.
Beneficial Qualifications & Skills
- Experience working in the financial services industry.
- Proficiency in Java as an additional programming language.
Education
- Bachelor's degree/University degree in Computer Science or a related field.
- Master's degree preferred.
Time Type: Full time
Citi is an equal opportunity employer, and qualified candidates will receive consideration without regard to their race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other characteristic protected by law. If you are a person with a disability and need a reasonable accommodation to use our search tools and/or apply for a career opportunity review Accessibility at Citi. View Citi's EEO Policy Statement and the Know Your Rights poster.
Senior AI Engineer, Vice President in London employer: Citibank (Switzerland) AG
Citi is an exceptional employer, offering a dynamic work environment in London that fosters innovation and collaboration. As the Global Head of Client Experience, you will lead a talented team dedicated to enhancing client satisfaction through cutting-edge AI analytics and a client-centric culture. With ample opportunities for professional growth and a commitment to employee development, Citi stands out as a leader in the financial services sector, making it an ideal place for those seeking meaningful and rewarding careers.
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We think you need these skills to ace Senior AI Engineer, Vice President in London
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 Citibank (Switzerland) AG.
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How to prepare for a job interview at Citibank (Switzerland) AG
✨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 Citibank (Switzerland) AG 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.
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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.
