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GenAI Full-Stack Engineer Lead

Job in New York, New York County, New York, 10261, USA
Listing for: Citi
Full Time position
Listed on 2026-10-13
Job specializations:
  • Software Development
    AI Engineer (Applied/Software), Machine Learning/ ML Engineer
Salary/Wage Range or Industry Benchmark: 156000 - 234000 USD Yearly USD 156000.00 234000.00 YEAR
Job Description & How to Apply Below
Location: New York

GenAI Full-Stack Engineer Lead Job Req :

Location(s):

Irving, Texas, United States, Jacksonville, Florida, United States

Job Type:

Hybrid

Posted:

Oct. 06, 2026

Discover your future at Citi

Working at Citi is far more than just a job. A career with us means joining a team of approximately 219,000 dedicated people from around the globe. At Citi, you’ll have the opportunity to grow your career, give back to your community and make a real impact.

Job Overview

We are seeking a results-driven Generative AI practitioner with end-to-end experience for the execution and deployment of cutting-edge Generative AI and agentic AI solutions across our enterprise-wide Controls Technology platform. In this role, you will be responsible for translating AI strategy into tangible, production-ready capabilities that enhance operational efficiencies and drive business value. We're looking for someone who combines deep technical expertise in generative AI - including context engineering, retrieval systems, knowledge graphs, and multi-agent orchestration - with a proven track record of successfully delivering complex technology projects.

This role centers on architecting and delivering solutions built on pre-trained and hosted foundation models, not on training or fine-tuning models.

Key Responsibilities
  • GenAI Delivery Leadership: Execute the delivery roadmap for generative and agentic AI projects, ensuring alignment with business objectives and timelines. Manage the project lifecycle from ideation and scoping to deployment and post-launch support.
  • Team Leadership & Mentorship: Build, mentor, and manage a high-performing team of AI engineers and specialists. Foster a culture of execution, collaboration, and continuous improvement to successfully deliver on the AI roadmap.
  • End-to-End Solution Delivery: Oversee the design, development, and deployment of robust, scalable, and production-ready GenAI and agentic applications. Ensure all solutions meet rigorous performance, security, and quality standards before and after deployment.
  • Agentic Solution Delivery: Drive the design and delivery of agentic workflows and multi-agent systems
    , establishing standards for agent harnesses
    , orchestration patterns, and reliable long-running agent execution across the platform.
  • Stakeholder & Program Management: Serve as the primary point of contact for GenAI delivery. Manage stakeholder expectations, communicate project progress, identify and mitigate risks, and ensure on-time and on-budget delivery.
  • Cross-Functional Partnership: Collaborate closely with Data Mesh, Cloud Architecture, MLOps/LLMOps, and business unit teams to ensure the seamless integration and operationalization of GenAI and agentic solutions into our existing technology ecosystem.
  • Technical Excellence & Best Practices: Drive the adoption of best practices in software development (CI/CD), LLMOps, agent observability, and project management (Agile/Scrum) within the AI team to ensure efficient and repeatable delivery.
  • Governance & Ethical Deployment: Implement and enforce robust governance and ethical AI frameworks throughout the delivery process - including guardrails, agent isolation/sandboxing, and responsible AI practices - ensuring compliance with data privacy standards and corporate policies.

Technical Skills

  • Programming

    Languages:

    Python (expert proficiency required)
  • Python Packages:
    Transformers, Lang Chain, Llama Index, Tensor Flow, PyTorch, Pandas, Num Py, Scikit-learn, Flask/Django, and other relevant data science, machine learning, and web development libraries.
  • Deep Learning Frameworks:
    Tensor Flow, Py Torch
  • LLMs:
    Llama, Gemini, GPT, and other advanced LLMs.
  • Vector Databases:
    Pinecone, Weaviate, Chroma, Faiss, PostgreSQL with vector extensions (pgvector).
  • Cloud Platforms: AWS, Azure, GCP
  • MLOps Tools: MLflow, Kubeflow, or similar.
  • Containerization:
    Docker, Kubernetes
  • CI/CD Tools:
    Git Hub Actions, Jenkins, or similar.
  • Version Control:
    Git
  • Data Visualization & Reporting:
    Tableau, Power BI, matplotlib, seaborn.
  • Databases: SQL and No

    SQL databases
Qualifications
  • 10+ years of overall experience.
  • 8+ years of experience in AI/ML, with at least 3 years in Generative AI (including agentic AI).
  • 5+ years of leadership experience managing technical teams and delivering complex software or AI solutions.
  • Extensive hands-on experience with AWS services and infrastructure related to AI/GenAI.
  • A strong portfolio of projects showcasing the successful delivery of AI solutions into a production business environment.

Education:

  • Bachelor's or…
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