Senior GenAI Engineer - Solutions Architecture

• Design, build, and deploy highly optimized Retrieval-Augmented Generation (RAG) and Context Engineering pipelines.
• Develop and implement sophisticated workflow agents and enterprise-integrated autonomous agents capable of recursive reasoning and autonomous task delegation.
• Execute the architectural vision for IT systems through major, complex architecture projects, ensuring conformance to enterprise standards.
• Develop and maintain technology roadmaps, staying current with emerging technologies and recommending strategic business directions.
• Provide technical leadership across teams and act as an advisor or mentor to junior team members.
• Translate complex business problems into sound, scalable technical solutions.
• Seamlessly integrate with existing APIs, tool sets, and data stores to create and utilize vector stores, knowledge graphs, and LLM knowledge bases.
• Establish robust governance frameworks, including logging, explainability, and custom evaluation pipelines using paired benchmarks to ensure AI quality and reliability.
• Ensure all AI deployments eliminate reasoning drift, prevent data leakage, and support critical regulatory delivery dates.
• Provide integrated systems planning and recommend innovative technologies to enhance current systems.
• Appropriately assess risk when business decisions are made, demonstrating particular consideration for the firm's reputation and safeguarding Citigroup, its clients and assets, by driving compliance with applicable laws, rules and regulations, adhering to Policy, applying sound ethical judgment regarding personal behavior, conduct and business practices, and escalating, managing and reporting control issues with transparency.

• 5+ years' experience in software engineering, with a minimum of 3+ years dedicated to scalable machine learning, LLMOps, or Generative AI systems in a highly regulated enterprise environment.
• Expert-level proficiency in Python and a strong command of a compiled, object-oriented language (e.g., Java, C++).
• Deep practical knowledge of LLM orchestration, embedding models, vector database architecture, and advanced evaluation techniques for hallucination reduction.
• Proven track record of modernizing legacy architecture and deploying distributed, containerized machine learning pipelines (e.g., Docker, Kubernetes) at scale.
• Strong understanding of enterprise security postures, including prompt injection defense, dynamic data masking, and compliance-driven software development lifecycles.
• Developed communication and diplomacy skills to guide, influence, and persuade colleagues and stakeholders.
• Sophisticated analytical thought to resolve issues in a variety of complex situations.
• Demonstrated ability to manage multiple activities, prioritize effectively, and meet tight deadlines.
• A self-starter with the initiative to master new tasks and technologies quickly, exhibiting a methodical approach and strong attention to detail.

Master's degree is considered a plus.

• 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
• discretionary and formulaic incentive and retention awards