Job description

About the Role We are looking for a Lead Generative AI Developer to join our COO Technology Division in New York. In this high-impact role, you will architect, develop, and operationalize cutting-edge Generative AI and Large Language Model (LLM) solutions that directly transform how Citi's operational teams work. You will collaborate with cross-functional stakeholders - including operations leads, data engineers, product managers, and enterprise architects to deliver enterprise-grade AI capabilities at scale. This is a hands-on engineering role for a builder who thrives at the intersection of applied AI research and production software engineering. Key Responsibilities • Design & Build GenAI Solutions: Architect and implement end-to-end Generative AI pipelines including LLM integrations, Retrieval-Augmented Generation (RAG) systems, autonomous AI agents, and prompt engineering frameworks. • Python Development: Develop robust, scalable, and production-ready Python services and APIs that power AI-driven features across COO platforms. • Model Integration & Fine-tuning: Evaluate, integrate, and fine-tune LLMs (e.g., GPT-5, Claude, Mistral) and embedding models for domain-specific financial use cases. • MLOps & Deployment: Build and maintain ML/GenAI deployment pipelines using modern MLOps practices, ensuring reliability, observability, and governance. • Agentic Workflows: Design and implement multi-agent orchestration frameworks (e.g., LangGraph, Google ADK) for complex, multi-step operational workflows. • Enterprise AI Governance: Collaborate with Citi's AI Risk and Compliance teams to ensure all AI solutions align with regulatory requirements, responsible AI frameworks, and data privacy standards. • Data Engineering: Design and optimize data pipelines feeding AI systems, working with vector databases (e.g., Pinecone, Weaviate, pgvector) and enterprise data platforms. • Technical Leadership: Mentor junior developers, lead code reviews, and contribute to GenAI standards and best practices across the COO Technology organization. • Stakeholder Collaboration: Translate complex business requirements from COO operations stakeholders into technical AI solutions, providing clear communication of trade-offs and timelines. Required Qualifications • Experience: 10+ years of professional software engineering experience, with at least 2+ years focused on Generative AI / LLM application development . • Python: Expert-level Python proficiency — including async programming, API development (FastAPI, Flask), and software design patterns. • GenAI & LLM Stack: • Deep hands-on experience with LLM frameworks: LangChain, LangGraph, LlamaIndex etc • Hands on experience with Google Cloud AI Platform • Proven experience with RAG architectures , embedding pipelines, and vector search • Strong understanding of prompt engineering, few-shot learning, and chain-of-thought techniques • Experience integrating with LLM APIs: OpenAI, Azure OpenAI, Anthropic, AWS Bedrock, or Google Vertex AI • Machine Learning: Solid grounding in ML fundamentals; familiarity with model evaluation, fine-tuning (LoRA, PEFT), and inference optimization. • Cloud Platforms: Hands-on experience with at least one major cloud provider — AWS, Azure, or GCP — particularly managed AI/ML services. • Data & Databases: Proficiency with SQL, NoSQL, and vector databases (Pinecone, Weaviate, Chroma, pgvector). • Software Engineering Practices: Strong understanding of CI/CD pipelines, containerization ( Docker, Kubernetes ), version control (Git), and automated testing. • Financial Services Acumen (Preferred): Prior experience in banking, fintech, or a regulated industry is a strong plus. Preferred Qualifications • Experience with multi-agent orchestration frameworks (MS AgentFramework, ADK, Strands, LangGraph) • Familiarity with MLflow, Weights & Biases, or similar experiment tracking and model management tools • Knowledge of responsible AI practices : bias detection, explainability, hallucination mitigation • Exposure to Kafka, Spark, or Airflow for data pipeline engineering • Experience working in an Agile/SAFe delivery environment • Advanced degree (M.S.) in Computer Science, AI/ML, or a related discipline — or equivalent demonstrated experience Technical Stack (Working Knowledge Expected) Languages : Python (expert), SQL, Bash GenAI Frameworks : LangChain, LlamaIndex, LangGraph, Semantic Kernel LLM Providers : OpenAI / Azure OpenAI, Anthropic, AWS Bedrock, Google Vertex AI Vector Databases : Pinecone, Weaviate, pgvector, Chroma Cloud : AWS / Azure / GCP MLOps : MLflow, Docker, Kubernetes, GitHub Actions Data Engineering : Spark, Airflow, Kafka Databases : PostgreSQL, MongoDB, Redis Education: • Bachelor’s degree/University degree or equivalent experience • Master’s degree preferred ------------------------------------------------------ Job Family Group: Technology ------------------------------------------------------ Job Family: Architecture ------------------------------------------------------ Time Type: Full time ------------------------------------------------------ Primary Location: New York New York United States ------------------------------------------------------ Primary Location Full Time Salary Range: $176,720.00 - $265,080.00 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. ------------------------------------------------------ Anticipated Posting Close Date: Aug 19, 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.

Requirements

Must-haves

This is a hands-on engineering role for a builder who thrives at the intersection of applied AI research and production software engineering.
Python Development: Develop robust, scalable, and production-ready Python services and APIs that power AI-driven features across COO platforms.
Model Integration & Fine-tuning: Evaluate, integrate, and fine-tune LLMs (e.g., GPT-5, Claude, Mistral) and embedding models for domain-specific financial use cases.
MLOps & Deployment: Build and maintain ML/GenAI deployment pipelines using modern MLOps practices, ensuring reliability, observability, and governance.
Agentic Workflows: Design and implement multi-agent orchestration frameworks (e.g., LangGraph, Google ADK) for complex, multi-step operational workflows.
Enterprise AI Governance: Collaborate with Citi's AI Risk and Compliance teams to ensure all AI solutions align with regulatory requirements, responsible AI frameworks, and data privacy standards.
Data Engineering: Design and optimize data pipelines feeding AI systems, working with vector databases (e.g., Pinecone, Weaviate, pgvector) and enterprise data platforms.
Technical Leadership: Mentor junior developers, lead code reviews, and contribute to GenAI standards and best practices across the COO Technology organization.
Stakeholder Collaboration: Translate complex business requirements from COO operations stakeholders into technical AI solutions, providing clear communication of trade-offs and timelines.
Experience: 10+ years of professional software engineering experience, with at least 2+ years focused on Generative AI / LLM application development .
Python: Expert-level Python proficiency — including async programming, API development (FastAPI, Flask), and software design patterns.
Deep hands-on experience with LLM frameworks: LangChain, LangGraph, LlamaIndex etc

Nice-to-haves

Financial Services Acumen (Preferred): Prior experience in banking, fintech, or a regulated industry is a strong plus.
Experience with multi-agent orchestration frameworks (MS AgentFramework, ADK, Strands, LangGraph)
Familiarity with MLflow, Weights & Biases, or similar experiment tracking and model management tools
Knowledge of responsible AI practices : bias detection, explainability, hallucination mitigation
Exposure to Kafka, Spark, or Airflow for data pipeline engineering
Experience working in an Agile/SAFe delivery environment
Advanced degree (M.S.) in Computer Science, AI/ML, or a related discipline — or equivalent demonstrated experience
Technical Stack (Working Knowledge Expected)
Languages : Python (expert), SQL, Bash
GenAI Frameworks : LangChain, LlamaIndex, LangGraph, Semantic Kernel
LLM Providers : OpenAI / Azure OpenAI, Anthropic, AWS Bedrock, Google Vertex AI
Vector Databases : Pinecone, Weaviate, pgvector, Chroma

Application prep

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Keywords to mirror

aillmpythonmlapiazureawsmachine learninggcpsqlci/cddockerkubernetesagileaccessibility

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Effort: medium

Benefits

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Dental

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401(K)

Paid Time Off

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