Senior AI/AML Engineer, Vice President

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Most Relevant Skills

Other Relevant Skills

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Automated Processing and AI

Qualifications

• 3+ years of experience in AI/ML engineering and over all engineering experience of 6+ years
• Strong proficiency in Python and backend development
• ADK (Agent Development Kit) for building and orchestrating agents
• LangChain or similar LLM frameworks
• LLM / GenAI systems (RAG, agents, tool chaining)
• Proven experience delivering production-grade systems in enterprise environments
• Strong understanding of API integration, distributed systems, and microservices architecture

Preferred Qualifications

• Experience working in regulated industries (Financial Services preferred)
• Experience building multi-agent systems with ADK or similar frameworks
• Familiarity with LLM platforms such as Gemini, OpenAI, or Vertex AI
• Knowledge of AML systems, financial crime detection, or compliance workflows
• Experience implementing AI guardrails, evaluation frameworks, and observability tools
• Exposure to real-time AI systems (voice, streaming, event-driven architectures)
• Experience with cloud platforms (GCP, AWS, Azure)
• Bachelor’s degree in Computer Science, Engineering, or related field
• Technology
• Technology Product Management
• Full time
• Irving Texas United States
• $138,720.00 - $208,080.00
• In addition to salary, Citi’s offerings may also include, for eligible employees, discretionary and formulaic incentive and retention awards. Citi offers competitive employee benefits, including: medical, dental & vision coverage; 401(k); life, accident, and disability insurance; and wellness programs. Citi also offers paid time off packages, including planned time off (vacation), unplanned time off (sick leave), and paid holidays. For additional information regarding Citi employee benefits, please visit citibenefits.com. Available offerings may vary by jurisdiction, job level, and date of hire.
• Most Relevant Skills
• Please see the requirements listed above.
• Other Relevant Skills
• For complementary skills, please see above and/or contact the recruiter.
• Oct 30, 2026
• Automated Processing and AI
• We use automated processing, including artificial intelligence, for our legitimate business interests (or our reasonable and appropriate business purposes) to identify and align the candidate's skills and abilities with a specific job opening. Additionally, if you so choose, or consent, we can match your skills and abilities to other suitable roles at Citi.
• Importantly, all our hiring processes and decisions, including determining your suitability for a role, are conducted, checked, and decided by individuals. Our automated processing and AI do not involve relying on automatic or autonomous decision-making. Please refer to any Jurisdictional Considerations, with specific provisions for your country (where relevant) for further details.
• Illinois residents – AI Notice and Right
• Citi is an equal opportunity employer, and qualified candidates will receive consideration without regard to their race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other characteristic protected by law.
• If you are a person with a disability and need a reasonable accommodation to use our search tools and/or apply for a career opportunity review Accessibility at Citi.
• View Citi’s EEO Policy Statement and the Know Your Rights poster.

Responsibilities

• Design and develop LLM-powered applications and agentic systems using frameworks such as LangChain and ADK (Agent Development Kit)
• Build and manage multi-agent orchestration, tool chaining, and workflow automation
• Develop robust guardrails (input/output validation) to ensure safe and compliant AI behavior
• Integrate AI solutions with enterprise APIs, data platforms, and internal systems
• Design real-time and asynchronous AI pipelines (REST APIs, streaming, WebSockets)
• Partner with Risk, Compliance, and Model Governance teams to support MRM validation and approvals
• Lead end-to-end delivery of AI solutions from concept through production deployment
• Provide technical leadership and mentorship to engineering teams
• Drive best practices, standards, and reusable frameworks for AI engineering
• Ensure observability, monitoring, and performance optimization of AI systems