Working at Citi is far more than just a job. A career with us means joining a team of more than 230,000 dedicated people from around the globe. At Citi, you’ll have the opportunity to grow your career, give back to your community and make a real impact.
The AI Engineer Intermediate Analyst is an intermediate-level professional responsible for designing and implementing complex, scalable AI solutions in coordination with the AI Innovation team. The overall objective is to apply a strong understanding of AI, software architecture, and business processes to build and optimize high-performance AI systems.
Responsibilities:
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Design and develop production-ready Generative AI and Agentic solutions, with a strong focus on Agent Architecture selection, memory management, hallucination control, and performance measurement.
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Analyze complex business processes and problems to design and implement technology and analytic solutions at scale, with a focus on performance optimization.
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Develop and maintain robust data and technology pipelines, ensuring they are scalable, efficient, and reliable.
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Implement feedback loops for AI agents using reinforcement learning techniques to continuously improve solution effectiveness.
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Take ownership of the technical design and implementation of AI features and services.
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Adhere to and promote best practices in software development, MLOps, and Model Governance.
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Mentor junior engineers and provide technical guidance on projects.
Qualifications:
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4-7 years of overall experience with a minimum of 2 years of experience in developing production-ready Gen AI based RAG or Agent-based solutions.
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Strong experience in designing Agentic solutions, including Agent Architecture selection, memory management, hallucination control, and measuring solution effectiveness.
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Proven ability to analyze business problems and design scalable technology/analytic solutions.
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Hands-on experience with performance optimization of highly scalable systems.
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Strong proficiency in Python and deep experience with AI/ML frameworks (PyTorch, TensorFlow, LangChain).
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Extensive experience with cloud platforms (AWS, Azure, GCP), containerization (Kubernetes), and MLOps tools.
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Experience with data pipeline and technology pipeline development.
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Excellent analytical skills and a deep understanding of software architecture principles.
Education:
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Bachelor's/University degree or equivalent experience in Computer Science, Engineering, or a related quantitative field.
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Job Family Group:
Decision Management
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Job Family:
Specialized Analytics (Data Science/Computational Statistics)
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Time Type:
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Most Relevant Skills
Please see the requirements listed above.
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Other Relevant Skills
For complementary skills, please see above and/or contact the recruiter.
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