Senior AI Data Engineer- Vice President

Citi • New York, NY

1d

About The Position

Agent Design and Development: Design and implement intelligent agents, including their perception, reasoning, planning, and action execution modules. System Architecture: Develop scalable and robust architectures for agentic systems, ensuring high performance, reliability, and security. Machine Learning Integration: Integrate various machine learning models (e.g., LLMs, reinforcement learning, predictive models) to enhance agent capabilities and decision-making. Task Automation: Develop agents that can automate complex tasks, optimize workflows, and solve real-world problems across various domains. Framework and Tooling: Utilize and contribute to agentic AI frameworks and development tools. Evaluation and Optimization: Design and implement metrics and evaluation strategies for agent performance, continuously optimizing and improving agent behavior. Research and Innovation: Stay abreast of the latest advancements in AI, particularly in agent-based systems, autonomous AI, and related fields, and propose innovative solutions. Collaboration: Work closely with cross-functional teams including AI researchers, data scientists, product managers, and software engineers to integrate agentic solutions into broader products and services. Documentation: Create comprehensive technical documentation for agent designs, implementations, and operational procedures.

Requirements

• 6+ years of professional experience in software development with a focus on AI, machine learning, or agent-based systems.
• Programming: Strong proficiency in Python, SQL; Java is a plus.
• Solid understanding of core AI concepts, including knowledge representation, automated planning, decision-making under uncertainty, and multi-agent systems.
• Experience with machine learning frameworks (e.g., TensorFlow, PyTorch) and relevant libraries (e.g., Scikit-Learn, NumPy, Pandas).
• Familiarity with large language models (LLMs) and their application in agentic systems.
• Familiarity with specific agent frameworks (e.g., LangChain, AutoGen, CrewAI, RAG) or research in multi-agent reinforcement learning.
• Experience in designing and implementing APIs for AI services.
• Software Engineering: Experience with software development best practices, including version control (Git), CI/CD pipelines, testing, and code reviews.
• Problem-Solving: Excellent analytical and problem-solving skills with a creative approach to complex challenges.
• Communication: Strong written and verbal communication skills, with the ability to articulate complex technical concepts to diverse audiences.
• Platforms: Experience with cloud platforms (AWS, Azure, GCP) and containerization technologies (Docker, Kubernetes).
• Bachelor's degree in computer science, artificial intelligence, robotics, or a related quantitative field, or equivalent experience

Nice To Haves

• Experience in finance industry a plus.
• Master's degree preferred

Responsibilities

• Design and implement intelligent agents, including their perception, reasoning, planning, and action execution modules.
• Develop scalable and robust architectures for agentic systems, ensuring high performance, reliability, and security.
• Integrate various machine learning models (e.g., LLMs, reinforcement learning, predictive models) to enhance agent capabilities and decision-making.
• Develop agents that can automate complex tasks, optimize workflows, and solve real-world problems across various domains.
• Utilize and contribute to agentic AI frameworks and development tools.
• Design and implement metrics and evaluation strategies for agent performance, continuously optimizing and improving agent behavior.
• Stay abreast of the latest advancements in AI, particularly in agent-based systems, autonomous AI, and related fields, and propose innovative solutions.
• Work closely with cross-functional teams including AI researchers, data scientists, product managers, and software engineers to integrate agentic solutions into broader products and services.
• Create comprehensive technical documentation for agent designs, implementations, and operational procedures.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 5,001-10,000 employees