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Salary
$73k – $211k per year (Estimated)
Location
Remote/Hybrid (London, United Kingdom)
Seniority
Senior
Employment
Full-Time
Overview
Company
Impact
Profile match
Citi is one of the largest banks in the world, tracing its lineage to the City Bank of New York founded in 1812 and taking its modern shape through the 1998 merger that created Citigroup. Its most distinctive asset is a cross-border payments and treasury network unmatched by any competitor, moving trillions of dollars a day for multinational corporations, governments and other banks across roughly ninety countries. Alongside that institutional franchise it runs markets and investment banking, wealth management and a United States personal bank, and has spent recent years simplifying itself by exiting consumer operations across Asia, Europe and Latin America.

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 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

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Job Family Group:

Technology

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Job Family:

Applications Development

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Time Type:

Full time

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Most Relevant Skills

Please see the requirements listed above.

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Other Relevant Skills

For complementary skills, please see above and/or contact the recruiter.

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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.

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