Group Manager Payments Engineering Manager – Intelligent Automation

Key Responsibilities

• Lead, coach, and develop a high-performing team of software engineers responsible for delivering intelligent automation solutions for Payments Operations and Client Servicing.
• Own end-to-end engineering delivery, including planning, design, development, testing, deployment, production support, and operational excellence.
• Define and execute the engineering roadmap for AI-enabled workflow automation solutions aligned with Payments Technology objectives and business priorities.
• Provide hands-on technical leadership by actively participating in architecture reviews, solution design, technology selection, engineering reviews, and key technical decisions.
• Design, build, and deliver scalable software solutions leveraging Generative AI, LLMs, AI agents, document intelligence, workflow orchestration, and automation technologies.
• Partner closely with Payments Operations, Product, Architecture, and Technology teams to identify high-value automation opportunities and translate business requirements into scalable engineering solutions.
• Drive adoption of modern engineering practices including cloud-native architectures, microservices, event-driven systems, CI/CD pipelines, DevOps, and platform engineering principles.
• Establish and enforce engineering standards for quality, scalability, resiliency, observability, security, maintainability, and operational excellence.
• Ensure all solutions comply with enterprise technology standards, AI governance requirements, regulatory expectations, cybersecurity controls, and risk management policies.
• Foster a culture of innovation, accountability, continuous learning, and technical excellence through mentoring, talent development, performance management, and hiring.

Required Qualifications

• 15+ years of software engineering experience delivering large-scale enterprise applications, platforms, and distributed systems.
• 5+ years of experience leading software engineering teams, including management of globally distributed engineering organizations.
• Proven hands-on experience designing, building, and deploying Generative AI, Large Language Models (LLMs), Agentic AI, intelligent automation, workflow automation, or document intelligence solutions into production environments with measurable business impact.
• Demonstrated ability to lead engineering teams while remaining actively engaged in architecture, technical design, software delivery, and engineering execution.
• Deep expertise in Java, Spring Boot, microservices architecture, API development, and distributed systems design.
• Strong experience with event-driven architectures, messaging platforms, and streaming technologies such as Kafka.
• Experience designing, deploying, and operating cloud-native applications utilizing Kubernetes, OpenShift, containers, and modern DevOps practices.
• Strong understanding of AI architecture patterns including Retrieval-Augmented Generation (RAG), orchestration frameworks, AI agents, tool integration, workflow automation, and human-in-the-loop processes.
• Demonstrated ability to drive engineering execution while maintaining high standards for quality, reliability, security, compliance, and operational excellence.
• Strong stakeholder management, communication, and influencing skills, with experience collaborating with senior business and technology leaders in highly regulated environments.

Why Join Citi

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