Senior AI Engineer, Vice President

Citigroup Inc.; Greater London; Hybrid; GBP 120,000 - 170,000; Full time

Job summary

Citigroup Inc. in London seeks a Senior AI Engineer to design and build agentic AI solutions for Funds Transfer Pricing and Financial Hedging. You will lead multi-agent system design and production-grade deployments at global scale.

You will integrate LLMs, planning, and retrieval augmented generation, optimize for low latency, and mentor junior engineers while shaping the AI technical strategy.

Qualifications

• Professional experience in software development and system design.
• Proficiency in Python and SQL with production-quality Agentic AI development.
• Hands-on with frameworks like LangChain, LlamaIndex, or equivalents.
• Experience architecting multi-agent systems using frameworks like Google ADK, LangGraph, AutoGen or CrewAI.

Responsibilities

• Design and orchestrate complex multi-agent systems where autonomous agents collaborate, coordinate, negotiate, and delegate tasks.
• Design and implement advanced planning and reasoning capabilities using knowledge graphs and rule-based/deterministic reasoning.
• Develop resilient agent architectures with feedback-driven improvement and dynamic replanning.
• Integrate LLMs, predictive models, and reasoning frameworks to expand agent capabilities.

Skills

Python

SQL

Agentic AI development

LangChain

LlamaIndex

multi-agent systems

Prompt engineering

Context engineering

Education

Bachelor's degree in Computer Science

Master's degree preferred

Tools

Google ADK

LangGraph

AutoGen

CrewAI

Vector DBs

Job description

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 systemsusing frameworks likeGoogle ADK, LangGraph, AutoGen or CrewAI. This includes hands-on experience withplanning/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 ofPrompt 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

Job Family Group:

Technology

Job Family:

Applications Development

Time Type:

Full time

Most Relevant Skills

Please see the requirements listed above.

Other Relevant Skills

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

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