GenAI Developer

We are looking for an enthusiastic Generative AI Developer to join our Controls Technology team and support the development and integration of generative AI solutions. In this hands-on role, you will work under the guidance of senior developers and AI architects to help build retrieval-grounded, context-aware, and increasingly agentic AI applications. You will contribute to reliable, AI-driven features while growing your expertise across the modern GenAI stack. This role focuses on applying pre-trained and hosted foundation models — through context engineering, RAG, knowledge graphs, and agentic workflows — rather than training or fine-tuning models. This is a growth-oriented role: you'll take ownership of well-scoped components, learn established patterns from senior engineers, and progressively increase your technical depth and independence. Key Responsibilities • Assist in building and integrating generative AI applications using pre-trained and hosted foundation models (via managed GenAI APIs and open-model endpoints). • Support the implementation of context engineering workflows — assembling system instructions, retrieved knowledge, tool definitions, and conversation memory into reliable, token-efficient prompts, following established patterns. • Contribute to prompt engineering (zero-shot, few-shot, chain-of-thought, role-based prompting) for AI-powered workflows. • Help develop and maintain Retrieval-Augmented Generation (RAG) components, including chunking, embedding, and semantic/keyword search. • Support the development of knowledge graph and Graph RAG pipelines under guidance to enable grounded, traceable responses. • Contribute to agentic workflows — helping build AI agents with tool-calling and basic planning/memory, using frameworks such as Google Agent Development Kit (ADK), LangGraph, or CrewAI. • Assist with integrating agents to external tools and data sources via the Model Context Protocol (MCP), with exposure to the Agent2Agent (A2A) protocol. • Support the deployment, monitoring, and maintenance of GenAI and agentic applications in production environments. • Perform data preprocessing, document ingestion, and basic API development for AI applications. • Collaborate with data scientists and engineers to integrate AI capabilities into products. • Participate in code reviews, testing, and documentation to ensure quality and reliability. • Stay curious about advancements in GenAI and agentic AI, and share learnings with the team. Required Technical Skills • Proficiency in Python for GenAI development, data preprocessing, and scripting. • Solid understanding of core generative AI concepts — foundation models, LLMs, tokenization, embeddings, and context windows. • Hands-on experience with prompt engineering; foundational understanding of context engineering techniques. • Practical experience (project or professional) building RAG systems, including chunking, vector databases, and semantic search. • Familiarity with knowledge graphs and interest in Graph RAG for relationship-aware retrieval. • Exposure to agentic AI development — building tool-using agents or multi-step workflows with a framework such as Google ADK, LangGraph, CrewAI, or the OpenAI Agents SDK. • Awareness of agent tooling and protocols, including tool/function calling and the Model Context Protocol (MCP); familiarity with the A2A protocol is a plus. • Basic understanding of agent harness concepts — session/state management, memory, and guardrails. • Experience consuming major GenAI APIs (e.g., OpenAI, Gemini, Claude) and exposure to orchestration frameworks such as LangChain or LlamaIndex. • Understanding of application deployment and containerization (Docker). • Working knowledge of version control systems (Git). • Awareness of AI compliance, data privacy, guardrails, and responsible AI principles. Required Soft Skills • Strong teamwork and communication abilities. • Eagerness to learn new AI/GenAI and agentic technologies and frameworks. • Analytical mindset and attention to detail. • Openness to feedback, coaching, and continuous improvement. Qualifications • Bachelor's or Master's degree in Computer Science, Data Science, AI, or a related field. • 4+ years of experience with min 2–4 years of professional experience in software/AI development, with exposure to Generative AI and agentic AI. • Experience contributing to AI/GenAI or software projects in a collaborative team setting. • Exposure to cloud-based AI/ML environments (AWS, GCP, or Azure) is a plus. ------------------------------------------------------ Job Family Group: Technology ------------------------------------------------------ Job Family: Applications Development ------------------------------------------------------ Time Type: Full time ------------------------------------------------------ Most Relevant Skills Please see the requirements listed above. ------------------------------------------------------ Other Relevant Skills For complementary skills, please see above and/or contact the recruiter. ------------------------------------------------------ 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. 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