AI Lead Engineer for 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) or Java (e.g., Spring Boot, Spring Cloud, Spring Security)
• Proficiency in UI (e.g., Angular, React, Next.js, Node.js, TypeScript) for full-stack development
• Proficiency in database technologies, such as Oracle, Postgres, or MongoDB
• 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., 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
• Work Experience: 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
• Education: Bachelor’s degree/University degree or equivalent experience
• Master’s degree preferred

Previous experience within the banking or financial services industry, understanding regulatory environments and specific challenges a plus

• medical, dental & vision coverage
• 401(k)
• life, accident, and disability insurance
• wellness programs
• paid time off packages, including planned time off (vacation), unplanned time off (sick leave), and paid holidays
• discretionary and formulaic incentive and retention awards