GenAI Full-Stack Engineer Lead

Posted 4 Days Ago
Be an Early Applicant
2 Locations
Hybrid
156K-234K Annually
Expert/Leader
Financial Services
The Role
Leads the delivery of production-ready generative and agentic AI solutions across an enterprise technology platform. Responsibilities include architecting multi-agent workflows, overseeing end-to-end application development and deployment, managing AI engineering teams, coordinating stakeholders and technical partners, enforcing security and governance standards, and advancing CI/CD, LLMOps, observability, and responsible AI practices. The role requires extensive AWS and AI/ML experience, strong Python expertise, and leadership of complex software or AI initiatives.
Summary Generated by Built In

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, LangChain, LlamaIndex, TensorFlow, PyTorch, Pandas, NumPy, Scikit-learn, Flask/Django, and other relevant data science, machine learning, and web development libraries.
  • Deep Learning Frameworks: TensorFlow, PyTorch
  • 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: GitHub Actions, Jenkins, or similar.
  • Version Control: Git
  • Data Visualization & Reporting: Tableau, Power BI, matplotlib, seaborn.
  • Databases: SQL and NoSQL 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 Master's degree in Computer Science, Data Science, AI, or a related field (PhD preferred).

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Job Family Group: Technology

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Job Family:Applications Development

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Time Type:Full time

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Primary Location:Irving Texas United States

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Primary Location Full Time Salary Range:$156,160.00 - $234,240.00


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.

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Most Relevant Skills Please see the requirements listed above.

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Other Relevant Skills For complementary skills, please see above and/or contact the recruiter.

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Anticipated Posting Close Date:Oct 13, 2026

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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

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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.

Skills Required

  • 10+ years of overall professional experience
  • 8+ years of experience in artificial intelligence and machine learning
  • At least 3 years of experience in generative AI, including agentic AI
  • 5+ years of leadership experience managing technical teams and delivering complex software or AI solutions
  • Expert proficiency in Python
  • Extensive hands-on experience with AWS services and AI/GenAI infrastructure
  • Portfolio demonstrating successful delivery of AI solutions into a production business environment
  • Bachelor's or Master's degree in Computer Science, Data Science, AI, or a related field
  • PhD in a related field
  • Experience with Transformers, LangChain, LlamaIndex, TensorFlow, PyTorch, Pandas, NumPy, Scikit-learn, Flask, Django, and related libraries
  • Experience with Llama, Gemini, GPT, and other large language models
  • Experience with vector databases including Pinecone, Weaviate, Chroma, Faiss, or pgvector
  • Experience with AWS, Azure, and GCP cloud platforms
  • Experience with MLflow, Kubeflow, or similar MLOps tools
  • Experience with Docker and Kubernetes
  • Experience with GitHub Actions, Jenkins, or similar CI/CD tools
  • Experience with Git version control
  • Experience with SQL and NoSQL databases
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The Company
HQ: New York, NY
226,610 Employees
Year Founded: 1998

What We Do

Citigroup is a global diversified financial services holding company serving consumers, corporations, governments and institutions. It provides consumer banking and credit, corporate and investment banking, securities brokerage, trade and securities services, and wealth management. Operating across nearly 160 countries and jurisdictions, Citi aims to be a leading partner for institutions with cross-border needs, a global wealth manager, and a valued personal bank in the United States.

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