Senior AI Engineer, Vice President

Job Overview

Responsibilities

• check_circle 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.
• check_circle 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.
• check_circle 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.
• check_circle Integrate large language models (LLMs), predictive models, and reasoning frameworks to expand agent capabilities, improve decision quality, and support complex business workflows.
• check_circle 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.
• check_circle Design and develop APIs, tools, and microservices that enable seamless integration of AI capabilities with enterprise applications, databases, and business platforms.
• check_circle 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.
• check_circle 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.
• check_circle 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.

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