SVP Apps Dev Tech Senior Lead Analyst

About the role

Citi is seeking a highly experienced Apps Dev Tech Senior Lead Analyst specializing in AI / AML Engineering to lead the development of enterprise-grade GenAI and agent-based solutions.

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

Qualifications

• 8–12+ years of experience in software engineering or 5+ years of AI/ML engineering
• Strong proficiency in Python and backend development
• Hands-on experience with: 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
• Experience working in regulated industries (Financial Services preferred)

Preferred Skills

• 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)