Generative AI Technology Specialist Vice President

Citi-posted 4 months ago
$113,840 - $170,760/Yr
Full-time • Senior
Tampa, FL
5,001-10,000 employees
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We are seeking a highly skilled GenAI Tech Specialist to join our innovative team in Tampa, FL. This critical role will focus on driving AI/ML advancements within our finance division, with a particular emphasis on document processing and analysis. You will be responsible for the end-to-end integration of GenAI solutions, from understanding data requirements to collaborating with cross-functional teams and deploying production-ready applications. This role requires demonstrable experience in implementing real-world GenAI products, particularly those involving structured and unstructured data[database & documents].

  • Design, develop, and deploy production-ready GenAI solutions for various financial applications, such as risk assessment, fraud detection, personalized financial advice, and automated reporting, with a focus on leveraging document-based information.
  • Work with both structured and unstructured financial data, including complex documents (PDFs, etc.), implementing techniques like NLP, information retrieval, and document parsing for data processing and analysis.
  • Define and gather data requirements for GenAI model training and evaluation.
  • Design and implement Retrieval Augmented Generation (RAG) pipelines, leveraging expertise in vector databases and prompt engineering, specifically for document retrieval and analysis.
  • Develop and deploy chatbot solutions and other conversational AI interfaces, integrating them with existing financial systems and document processing workflows.
  • Utilize dynamic SQL to interact with relational databases, extracting and manipulating data for integration into GenAI pipelines, including data extracted from documents.
  • Write high-quality, well-documented, and testable Python code, adhering to best practices for software development.
  • Evaluate and integrate emerging GenAI technologies and tools, including the latest LLMs like Llama 3, Gemini, and exploring emerging models like Llama 4.
  • Stay abreast of advancements in Agentic AI and assess their applicability to financial use cases, particularly in document processing.
  • Define and track key metrics to evaluate the performance and impact of GenAI solutions, especially those related to document processing accuracy and efficiency.
  • Collaborate effectively with Model Risk Management (MRM), the AI Center of Excellence (COE), and other cross-functional teams to ensure successful integration and deployment of GenAI products.
  • Collaborate closely with stakeholders to translate business needs into effective technical solutions using GenAI, with a focus on addressing document-centric challenges.
  • Contribute to the development and maintenance of MLOps pipelines, ensuring the scalability and reliability of deployed models, including those used for document processing.
  • Bachelor's or Master's degree in Computer Science, Engineering, or a related field. A degree specializing in AI/ML is a significant plus. Ph.D. preferred.
  • 10+ years of experience in AI/ML, with at least 3 years of specialized experience in Generative AI, including demonstrated success in deploying production-ready GenAI solutions, preferably with a focus on document processing.
  • Expert-level proficiency in Python.
  • Deep understanding and hands-on experience with Transformers, LangChain, Llama 3, Llama 4, Gemini, GPT-4+, and other relevant libraries.
  • Proficiency in NumPy, Pandas, SciPy, Scikit-learn, TensorFlow, PyTorch.
  • Expertise in designing and implementing RAG pipelines using vector databases like Postgres, Pinecone, Weaviate, Faiss, and Chroma.
  • Experience with PDF parsing libraries, chunking techniques, re-ranking algorithms, and table transformers.
  • Strong NLP skills for text extraction, analysis, and understanding from documents.
  • Proficiency in SQL and dynamic SQL for relational databases (e.g., PostgreSQL, MySQL, SQL Server). Experience with NoSQL databases is a plus.
  • Familiarity with major cloud providers (AWS, Azure, GCP) and MLOps tools like MLflow, Kubeflow, and CI/CD pipelines.
  • Strong understanding of software engineering principles, including version control (Git), testing, and code quality.
  • Excellent communication and collaboration skills.
  • Knowledge of Agentic AI and other emerging trends in GenAI.
  • Strong analytical and problem-solving abilities.
  • Experience in the financial industry.
  • Familiarity with specific GenAI applications in finance (e.g., algorithmic trading, risk management).
  • Contributions to open-source projects.
  • 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
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