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Job Overview
We are building the most consequential AI solutions in Funds Transfer Pricing and Financial Hedging platforms, and we are seeking a Lead AI Engineer to own the technical vision and drive the execution for these domains.
In this position, you will be accountable for the end-to-end technical success of our agentic solutions, from architectural vision and design through implementation and adoption, ensuring they deliver scalable, resilient, and business-impacting capabilities at global scale.

Responsibilities:

Strategy & Technical Ownership

• Define and own the end-to-end technical strategy for agentic AI within the Funds Transfer Pricing and Financial Hedging domains, ensuring alignment with both business objectives and the firm's technology standards.
• Serve as the ultimate technical authority on agentic systems, providing expert guidance to senior leadership and translating complex business challenges into a clear, actionable technical roadmap.
• Lead by example through hands-on coding, personally architecting and contributing to the most critical and complex components of the system, setting the standard for code quality and innovation.
• Mentor and cultivate a team of senior AI engineers, fostering a culture of technical excellence, continuous learning, and collaborative problem-solving.

System Architecture & Design

• Own the architectural vision for highly scalable, resilient, and performant multi-agent systems, establishing the blueprint and design patterns that will be used across the platform.
• Oversee the design of intelligent agentic systems, including reasoning, planning, memory, orchestration, and action execution, ensuring they are scalable, reliable, auditable, and fit for business-critical workflows

Development Guidance & Implementation

• Guide the team in implementing robust AI agents while personally driving the development of core components and complex features.
• Set the strategy for integrating advanced technologies, including large language models (LLMs), predictive models, and sophisticated reasoning frameworks, to continuously expand agent capabilities.
• Establish and enforce best practices for designing and optimizing Retrieval-Augmented Generation (RAG) architectures and vector data strategies.

Quality, Performance & Governance

• Own the comprehensive strategy for AI system quality, defining the frameworks and metrics for measuring and optimizing agent performance, reliability, and task success.
• Establish and enforce rigorous standards for AI governance, explainability (XAI), and responsible AI, ensuring systems are transparent, auditable, and compliant.

Required Qualifications & Skills

• Extensive professional experience in software development and system design, with at least 5 years in a technical leadership capacity, guiding senior engineering teams in delivering large-scale, complex systems.
• Architectural Mastery of the AI Ecosystem: A proven track record of architecting solutions with the modern AI ecosystem. This requires deep, hands-on expertise with frameworks for agent development (Google ADK), multi-agent orchestration (LangGraph, AutoGen, CrewAI), and data augmentation (LangChain, LlamaIndex).
• Proven Expertise in Agentic Systems: A track record of architecting and delivering complex single- and multi-agent systems, demonstrating expertise in planning/reasoning engines, memory systems, and agentic protocols like MCP.
• Deep, Practical Knowledge of LLMs: Demonstrated mastery of LLM fundamentals, Prompt Engineering, and Context Engineering, with a history of applying this knowledge to build sophisticated agentic architectures and design robust APIs for AI services.
• Deep expertise in enterprise Retrieval-Augmented Generation (RAG) architectures, including document ingestion, embedding strategies, retrieval optimization, reranking, vector databases, and context management.
• Expert-Level Engineering Craftsmanship: Expert-level proficiency in Python and SQL applied to building production-quality, high-performance AI systems.
• Proven ability to lead technical strategy, influence senior stakeholders, drive architecture decisions across multiple teams, and mentor senior engineers and technical leads.

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
• Master's degree preferred

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Job Family Group:
Technology ------------------------------------------------------

Job Family:
Applications Development ------------------------------------------------------

Time Type:
Full time ------------------------------------------------------

Most Relevant Skills
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Other Relevant Skills
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