Gen AI Developer - Vice President

Citi • Irving, TX

2d

About The Position

Gen AI Developer is a senior level position responsible for establishing and implementing new or revised application systems and programs in coordination with the Technology team. The overall objective of this role is to lead applications systems analysis and programming activities. Responsibilities: Partner with multiple management teams to ensure appropriate integration of functions to meet goals as well as identify and define necessary system enhancements to deploy new products and process improvements Resolve variety of high impact problems/projects through in-depth evaluation of complex business processes, system processes, and industry standards Provide expertise in area and advanced knowledge of applications programming and ensure application design adheres to the overall architecture blueprint Utilize advanced knowledge of system flow and develop standards for coding, testing, debugging, and implementation Develop comprehensive knowledge of how areas of business, such as architecture and infrastructure, integrate to accomplish business goals Provide in-depth analysis with interpretive thinking to define issues and develop innovative solutions Serve as advisor or coach to mid-level developers and analysts, allocating work as necessary Appropriately assess risk when business decisions are made, demonstrating particular consideration for the firm's reputation and safeguarding Citigroup, its clients and assets, by driving compliance with applicable laws, rules and regulations, adhering to Policy, applying sound ethical judgment regarding personal behavior, conduct and business practices, and escalating, managing and reporting control issues with transparency. Recommended Qualifications: Experience: 8+ Years in Python and AI (with 2+ year focused on GenAI/Agentic runtime) Key Responsibilities: AI Agent Development: Build and orchestrate AI agents using frameworks like LangChain, AutoGen, or CrewAI, implementing self-healing workflows (e.g., Act-Verify-Refine loops). LLM Integration & Backend: Develop robust backend systems using Python and TypeScript, integrating LLMs into microservices architectures. Data Management for LLMs: Utilize vector databases (Pinecone, Milvus, Weaviate) for agent memory and architect Retrieval-Augmented Generation (RAG) pipelines to enhance LLM accuracy and contextual understanding. Prompt Engineering: Design and optimize prompt strategies, including automated evaluation frameworks, for high-quality LLM output. Context Engineering: Manage LLM information ecosystems, including system prompts, RAG implementation, and conversation history. MLOps & Deployment: Oversee the end-to-end lifecycle of generative models, focusing on inference speed, cost-efficiency, and scalability on cloud platforms (AWS, GCP, Azure). AI Ethics & Compliance: Ensure adherence to security standards, IP regulations, and safety guidelines for all generative models. Tool Orchestration: Define and manage the API/tool access for AI agents to optimize accuracy.

Requirements

• 8+ Years in Python and AI (with 2+ year focused on GenAI/Agentic runtime)
• Strong command of Python, PyTorch, TensorFlow, and Hugging Face libraries
• Hands-on experience with LangChain, LlamaIndex, vector databases, and fine-tuning techniques (LoRA, QLoRA)
• Proven ability to integrate AI models into web applications via APIs (OpenAI, Anthropic)
• Solid understanding of software engineering best practices, including Git, CI/CD, and Docker
• Bachelor’s degree/University degree or equivalent experience

Nice To Haves

• Experience with multimodal AI models (image, video, audio generation)
• Published AI/LLM research or contributions to open-source AI projects
• Background in AI governance or safety policy development

Responsibilities

• Partner with multiple management teams to ensure appropriate integration of functions to meet goals as well as identify and define necessary system enhancements to deploy new products and process improvements
• Resolve variety of high impact problems/projects through in-depth evaluation of complex business processes, system processes, and industry standards
• Provide expertise in area and advanced knowledge of applications programming and ensure application design adheres to the overall architecture blueprint
• Utilize advanced knowledge of system flow and develop standards for coding, testing, debugging, and implementation
• Develop comprehensive knowledge of how areas of business, such as architecture and infrastructure, integrate to accomplish business goals
• Provide in-depth analysis with interpretive thinking to define issues and develop innovative solutions
• Serve as advisor or coach to mid-level developers and analysts, allocating work as necessary
• Appropriately assess risk when business decisions are made, demonstrating particular consideration for the firm's reputation and safeguarding Citigroup, its clients and assets, by driving compliance with applicable laws, rules and regulations, adhering to Policy, applying sound ethical judgment regarding personal behavior, conduct and business practices, and escalating, managing and reporting control issues with transparency
• Build and orchestrate AI agents using frameworks like LangChain, AutoGen, or CrewAI, implementing self-healing workflows (e.g., Act-Verify-Refine loops)
• Develop robust backend systems using Python and TypeScript, integrating LLMs into microservices architectures
• Utilize vector databases (Pinecone, Milvus, Weaviate) for agent memory and architect Retrieval-Augmented Generation (RAG) pipelines to enhance LLM accuracy and contextual understanding
• Design and optimize prompt strategies, including automated evaluation frameworks, for high-quality LLM output
• Manage LLM information ecosystems, including system prompts, RAG implementation, and conversation history
• Oversee the end-to-end lifecycle of generative models, focusing on inference speed, cost-efficiency, and scalability on cloud platforms (AWS, GCP, Azure)
• Ensure adherence to security standards, IP regulations, and safety guidelines for all generative models
• Define and manage the API/tool access for AI agents to optimize accuracy

Benefits

• 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

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 5,001-10,000 employees