Principal Generative AI Engineering Lead - Senior Vice President

Citi • Irving, TX

11d • $156,160 - $234,240

About The Position

The USCC Architecture and AI Engineering group is seeking a seasoned technical leader to guide its team and architect the next generation of intelligent systems. This pivotal role drives AI project execution from conceptualization through production, designing and delivering robust, scalable, and well-governed AI solutions. The successful candidate will mentor engineers, collaborate with business stakeholders, and steer technical direction in Generative and Agentic AI.

The role leads the architecture of complex end-to-end AI systems and partners with business leaders and product managers to identify high-impact opportunities, establish roadmaps, and translate business needs into a technical vision. It manages and develops an AI engineering team, establishes AI governance and MLOps practices, and remains hands-on in development. The lead also champions research and proof-of-concept initiatives and oversees MLOps strategy, deployment, monitoring, and lifecycle management in containerized environments such as OpenShift.

The position calls for deep expertise in Generative AI, machine learning, data pipelines, architecture, and production MLOps. The technical stack includes leading LLMs, AI frameworks, multi-agent orchestration, Python services, RAG and vector databases, ML/DL platforms, deployment and monitoring tools, and prompt engineering. The listed primary location is Irving, Texas. The full-time salary range is $156,160 to $234,240.

Requirements

• At least 6 years of experience in Generative AI application development, building and deploying solutions with LLMs such as GPT, Gemini, Claude, and Llama.
• Proven technical leadership or team management experience, including mentoring engineers, managing project priorities, and driving team performance.
• Demonstrated ability to design scalable, highly available, end-to-end AI and machine learning systems.
• Significant experience working with non-technical business stakeholders to identify opportunities, define requirements, and articulate AI strategy.
• Strong understanding and practical experience implementing governance, risk, and ethical guidelines for enterprise AI solutions.
• Expert-level Python skills and experience with its core AI/ML ecosystem, such as NumPy, Pandas, and Scikit-learn.
• Extensive hands-on experience implementing machine learning, deep learning, Generative AI, and Agentic AI systems.
• Expertise designing and managing complex data handling, preprocessing, and validation pipelines for mission-critical AI applications.
• Practical MLOps experience, including Docker, OpenShift or Kubernetes, CI/CD, and production deployment of AI models.
• Bachelor's degree or equivalent practical experience.
• Hands-on and strategic experience with LLMs including Gemini, OpenAI GPT models, Copilot, Claude, Llama, and local models.
• Experience with LangChain, LlamaIndex, and the Hugging Face ecosystem, including Transformers, Datasets, and Tokenizers.
• Experience with LangGraph and designing and building complex multi-agent systems.
• Experience building production-grade scalable services using Python, FastAPI, and asynchronous programming patterns.
• Experience designing advanced RAG techniques using vector databases such as Pinecone or Chroma and PostgreSQL with pgvector.
• Experience with PyTorch and/or TensorFlow for building and fine-tuning models at scale.
• Experience deploying resilient production APIs and implementing monitoring, logging, and alerting strategies.
• Mastery of advanced prompt engineering, AI workflow design, and Generative AI application optimization for cost, latency, and performance.

Responsibilities

• Lead the design and architecture of complex, end-to-end AI systems that are scalable, resilient, maintainable, and secure.
• Partner with business leaders and product managers to identify AI opportunities, define project roadmaps, and translate business needs into a technical vision.
• Manage, mentor, and develop AI engineers; guide project work and foster innovation, technical excellence, and continuous learning.
• Establish and enforce AI governance frameworks and MLOps best practices for ethical, responsible, and compliant AI implementations.
• Provide hands-on technical leadership in implementing machine learning, deep learning, and Generative AI models and maintaining code quality.
• Research emerging AI technologies, tools, and methodologies; lead proof-of-concept initiatives and recommend strategic integrations.
• Define and lead MLOps strategy, including deployment, monitoring, and lifecycle management of AI applications in containerized environments such as OpenShift.

Benefits

• Medical coverage
• Dental coverage
• Vision coverage
• 401(k)
• Life, accident, and disability insurance
• Wellness programs
• Paid time off, including planned vacation and unplanned sick leave
• Paid holidays
• Eligible employees may receive discretionary and formulaic incentive and retention awards

What This Job Offers

• Job Type: Full-time
• Career Level: Senior