AI Engineer

Discover your future at Citi

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Job Overview

The AI Engineer Associate is a developing professional responsible for designing, building, and deploying Generative AI applications in coordination with the AI Innovation team. The overall objective is to leverage a foundational understanding of full-stack development and AI principles to build and maintain production-grade AI solutions.

Responsibilities:

• Develop and deploy production-grade Generative AI applications, with a strong focus on building highly effective prompts, semantic search solutions, and robust RAG/Agentic pipelines.
• Engage in full-stack development, contributing to both the front-end and back-end of AI-powered applications.
• Implement and maintain MLOps pipelines for continuous integration, delivery, and monitoring of AI models.
• Contribute to the end-to-end ML model development lifecycle, including data understanding, feature engineering, algorithm selection, and validation.
• Collaborate with cross-functional teams to translate business requirements into technical solutions.
• Write clean, scalable, and well-documented code, adhering to software development best practices.
• Assist in evaluating and integrating new AI technologies and frameworks to enhance existing solutions.

Qualifications:

• 2-4 years of overall experience with a minimum of 1.5 years of experience in developing production-grade Gen AI based RAG solutions or Agent-based solutions.
• Proven experience as a full-stack developer, with hands-on experience in building and deploying production-ready applications.
• Strong understanding of the Gen AI development process, including prompt engineering, semantic search, and RAG/Agentic pipeline development.
• Proficiency in Python and experience with relevant frameworks (e.g., Flask, FastAPI, LangChain, Hugging Face).
• Experience with deep learning frameworks such as PyTorch or TensorFlow.
• Hands-on experience with at least one major cloud platform (AWS, Azure, or GCP) and containerization technologies (Docker, Kubernetes).
• Familiarity with MLOps principles and tools (e.g., MLflow, Kubeflow, Sagemaker).
• Strong problem-solving skills and the ability to work independently on assigned tasks.

Education:

• 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:

Full time

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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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