Svp - Artificial Intelligence Lead Engineer - Banking Technology

• Spearhead the end-to-end design, hands-on implementation, and deployment of scalable, robust agentic AI frameworks and generative AI solutions for critical banking use cases, ensuring high performance, reliability, and security
• Build full-stack applications that seamlessly integrate state-of-the-art ML/LLM tools and services into comprehensive AI solutions
• Champion an MVP-first approach, focusing on rapid iterations, hypothesis testing, and A/B experiments to achieve continuous improvement and quick time to value
• Design and implement rigorous metrics and evaluation strategies for AI system and agent performance, driving continuous optimization and behavioral improvement
• Proactively explore, prototype (POC), and integrate the latest advancements in AI, particularly in agent-based systems, autonomous AI, and generative AI technologies
• Provide hands-on technical leadership, guiding architectural decisions, and fostering collaboration with cross-functional teams including AI researchers, data scientists, product managers, and software engineers to integrate and scale AI solutions across Citi's products and services
• Exhibit excellent communication and collaboration skills, effectively engaging with diverse stakeholders

• Deep hands-on experience in engineering and executing scalable enterprise solutions
• Expert-level proficiency in Python (e.g., FastAPI, Django, Flask, PySpark)
• Solid understanding of core AI concepts, including knowledge representation, automated planning, decision-making under uncertainty, and multi-agent systems
• Hands-on experience with relevant frameworks (e.g., Google ADK, LanGraph, LangChain, AutoGen, CrewAI, N8N)
• Extensive experience with machine learning frameworks (e.g., TensorFlow, PyTorch) and relevant libraries (e.g., Scikit-Learn, NumPy, Pandas)
• Proven experience in creating, deploying, and integrating MCPs (Model Context Protocol) into agentic AI systems
• Deep familiarity with large language models (LLMs) such as ChatGPT, Claude, Gemini, and Llama, including their application within agentic systems
• Demonstrated experience in designing and implementing robust APIs for AI services
• Proficient in software development best practices, including version control (Git), CI/CD pipelines, comprehensive testing, and code reviews
• Strong understanding of agile methodologies, application resiliency, and security principles applied to complex AI projects
• Proven expertise in system design, application development, and ensuring operational stability for AI initiatives
• Deep experience with application and data architecture patterns and designs
• Experience leveraging managed services and existing platforms, with a strong emphasis on API-First Design, microservices, and event-driven architectures
• Hands-on experience with Docker and Kubernetes
• Excellent analytical and innovative problem-solving skills, with a pragmatic and creative approach to overcoming complex technical challenges
• Previous experience within the banking or financial services industry, understanding regulatory environments and specific challenges a plus
• Proficiency in database technologies, such as Oracle, Postgres, or MongoDB
• 10+ years of progressive software engineering experience with a strong emphasis on hands-on coding, demonstrating a proven track record of rapid delivery and successfully launching multiple AI features into production environments
• Minimum 3+ years of dedicated professional experience in software development focused on AI, prompt engineering, machine learning, Generative and/or agentic AI systems
• Strong hands-on experience with architecting and delivering enterprise scale AI projects
• Motivated self-starter with the ability to quickly learn new skills and effectively navigate complex organizational structures
• Bachelor’s degree in Computer Science, Information Technology, Artificial Intelligence, Robotics, or a related quantitative field
• a Master's degree is preferred

• Proficiency in UI (e.g., Angular, React, Next.js, Node.js, TypeScript) for full-stack development
• Java (e.g., Spring Boot, Spring Cloud, Spring Security)

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