We are seeking an experienced and highly skilled Senior GenAI Engineer to join our innovative team. The ideal candidate will have over 5 years of hands-on experience in generative AI development, with a strong background in agentic AI systems, large language models (LLMs), and advanced Python programming. This role requires exceptional technical skills, the ability to lead complex GenAI projects, and a passion for pushing the boundaries of AI capabilities.
Key Skills for This Role
PythonLangchainLangraphLangsmithGoogle Agent Development Kit (ADK)TensorFlow
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Job Overview
We are seeking an experienced and highly skilled Senior GenAI Engineer to join our innovative team. The ideal candidate will have over 5 years of hands-on experience in generative AI development, with a strong background in agentic AI systems, large language models (LLMs), and advanced Python programming. This role requires exceptional technical skills, the ability to lead complex GenAI projects, and a passion for pushing the boundaries of AI capabilities.
Key Responsibilities
Generative AI Solution Development: Design, develop, and deploy cutting-edge generative AI models and applications, focusing on leveraging Agentic AI principles to create autonomous and intelligent systems.
Agentic AI System Design: Architect and implement multi-agent systems and AI agents capable of complex reasoning, planning, and execution in dynamic environments.
LLM Integration and Customization: Integrate and fine-tune large language models (LLMs) into applications, ensuring optimal performance, accuracy, and ethical alignment.
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Python Development: Write robust, scalable, and efficient Python code for GenAI model development, data preprocessing, application logic, and API integrations.
Framework Utilization (Langchain, Langraph, Langsmith): Expertly apply and extend GenAI frameworks and tools such as Langchain for orchestration, Langraph for agentic workflow visualization, and Langsmith for debugging and evaluation of LLM applications.
Google ADK Implementation: Utilize the Google Agent Development Kit (ADK) to build, deploy, and manage AI agents within Google Cloud ecosystems.
Research and Innovation: Stay updated with the latest advancements in generative AI, agentic AI, and related fields. Experiment with new technologies and methodologies to continuously improve our GenAI offerings.
Performance Optimization: Optimize GenAI models and agentic systems for performance, scalability, and cost-efficiency in production environments.
Documentation and Best Practices: Develop and maintain comprehensive documentation for GenAI models, architectures, and applications. Establish and enforce best practices for GenAI development, testing, and deployment.
Collaboration and Mentorship: Collaborate with cross-functional teams including product managers, data scientists, and MLOps engineers. Provide mentorship and guidance to junior developers on GenAI best practices and emerging technologies.
Required Skills and Qualifications
Education: Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related quantitative field.
Experience: Minimum of 4 years of hands-on experience in Generative AI development, with a significant focus on Agentic AI systems.
Technical Skills: Advanced proficiency in Python programming. Demonstrated experience with large language models (LLMs) and their application. Strong practical experience with GenAI frameworks such as Langchain, Langraph, and Langsmith. Experience with Google Agent Development Kit (ADK). Familiarity with deep learning frameworks (e.g., TensorFlow, PyTorch). Experience with cloud platforms (GCP preferred) and MLOps practices. Solid understanding of data structures, algorithms, and software design principles.
Advanced proficiency in Python programming.
Demonstrated experience with large language models (LLMs) and their application.
Strong practical experience with GenAI frameworks such as Langchain, Langraph, and Langsmith.
Experience with Google Agent Development Kit (ADK).
Familiarity with deep learning frameworks (e.g., TensorFlow, PyTorch).
Experience with cloud platforms (GCP preferred) and MLOps practices.
Solid understanding of data structures, algorithms, and software design principles.
Analytical Skills: Exceptional analytical and problem-solving skills, with the ability to translate complex business requirements into scalable GenAI solutions.
Communication: Excellent verbal and written communication skills, with the ability to articulate complex technical concepts to both technical and non-technical stakeholders.
Innovation: A strong track record of driving innovation and implementing novel solutions in the AI space.
Preferred Qualifications
Experience with microservices architecture and API design.
Familiarity with containerization technologies (Docker, Kubernetes).
Prior experience in financial services or a highly regulated industry.
Contributions to open-source GenAI projects or relevant publications.
Leadership: Demonstrated experience in leading GenAI projects or mentoring development teams.
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.
About Citi
Banking219000 employeesFounded 1812
Global financial services organization enabling growth and economic progress.
