This is an intermediate level position responsible for participation in the establishment and implementation of new or revised application systems and programs in coordination with the Technology team. The overall objective of this role is to contribute to applications systems analysis and programming activities.
Qualifications:
7-11 years of relevant Python application development experience experience with strong exposure to Generative AI
Strong programming skills in Python, and familiarity with libraries like Transformers, Pandas, scikit-learn, Seaborn, Lang Chain, LlamaIndex, PyTorch, or TensorFlow.
Experience building applications with Open AI, Anthropic Claude, Google Gemini, or opensource LLMs.
Working knowledge of retrieval-augmented generation (RAG) pipelines and vector databases.
Understanding of ML Ops, model evaluation, prompt tuning, and deployment pipelines.
Build and tune LLM-based applications using platforms like Vertex, GPT, Lamma, Hugging Face, etc.
Create robust prompt engineering strategies and reusable prompt templates.
Integrate generative AI with enterprise applications using APIs, knowledge graphs, vector
databases (e.g., PG Vector, Neo4j, Mongodb), and orchestration tools.
Experience in systems analysis and programming of software applications
Experience in managing and implementing successful projects
Working knowledge of consulting/project management techniques/methods
Ability to work under pressure and manage deadlines or unexpected changes in expectations or requirements
Education:
Bachelor’s degree/University degree or equivalent experience
This job description provides a high-level review of the types of work performed. Other job-related duties may be assigned as required.
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Job Family Group: Technology------------------------------------------------------
Job Family:Applications Development------------------------------------------------------
Time Type:Full time------------------------------------------------------
Most Relevant Skills Please see the requirements listed above.------------------------------------------------------
Other Relevant Skills For complementary skills, please see above and/or contact the recruiter.------------------------------------------------------
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Skills Required
- 7-11 years of Python application development experience with strong exposure to Generative AI
- Strong programming skills in Python and familiarity with Transformers, Pandas, scikit-learn, Seaborn, LangChain, LlamaIndex, PyTorch, or TensorFlow
- Experience building applications with OpenAI, Anthropic Claude, Google Gemini, or open-source LLMs
- Working knowledge of retrieval-augmented generation (RAG) pipelines and vector databases
- Understanding of ML Ops, model evaluation, prompt tuning, and deployment pipelines
- Experience building and tuning LLM-based applications using platforms like Vertex, GPT, Llama, Hugging Face
- Create robust prompt engineering strategies and reusable prompt templates
- Integrate generative AI with enterprise applications using APIs, knowledge graphs, vector databases (e.g., PG Vector, Neo4j, MongoDB), and orchestration tools
- Experience in systems analysis and programming of software applications
- Experience in managing and implementing successful projects
- Working knowledge of consulting/project management techniques/methods
- Ability to work under pressure and manage deadlines or unexpected requirement changes
- Bachelor's degree or equivalent experience
Citi Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Citi and has not been reviewed or approved by Citi.
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Healthcare Strength — Benefits coverage is positioned as comprehensive, including health, dental, and vision insurance plus on-site clinics, prescription drug support, and disability coverage. Family-building support such as fertility assistance is described as a notable differentiator within the overall package.
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Retirement Support — Retirement benefits are framed as strong, highlighted by a 401(k) with matching and additional plan options like a Roth 401(k). Financial support is reinforced through discounts and broader financial guidance resources tied to the benefits ecosystem.
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Wellbeing & Lifestyle Benefits — Wellbeing support extends beyond insurance through programs like an Employee Assistance Program, counseling/legal resources, and gym or wellness reimbursement. These offerings increase the perceived total rewards value even when cash compensation sentiment varies by role.
Citi Insights
What We Do
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