Citi
GenAIPythonDeveloper
Neural analysis suggests this role is
optimal for Mid candidates.
“Gen AI Python Developer at Citi. Skills: Gen AI, Python, LLMs, MLOps. Participate in establishment of new application systems. Implement new application systems”
Industry & Context.
problem-solving abilities; work independently on complex, ambiguous problems
What They're Looking For.
Must Have
4-8 years of relevant experience in Apps Development or systems analysis role, foundational knowledge in Machine Learning (ML modeling), Data Science, Statistics, and AI fundamentals, including Natural Language Processing (NLP), Neural Networks, and Large Language Models (LLMs), Extensive hands-on experience with leading LLMs such as Google Gemini, OpenAI models, Anthropic Claude, Mistral, Llama, and various other open-source LLMs, Deep working knowledge and hands-on experience with Retrieval-Augmented Generation (RAG) pipelines, including advanced RAG techniques and their detailed implementation, Proven ability to build, tune, and deploy LLM-based applications using platforms like Vertex AI, Hugging Face, etc., Expertise in developing robust prompt engineering strategies, prompt tuning, and creating reusable prompt templates, Hands-on experience with agentic framework-based use case implementation, Working knowledge of Guardrails and methodologies for assessing the performance and safety of GenAI features, programming proficiency in Python, including extensive experience with libraries such as Pandas, NumPy, scikit-learn, PyTorch, TensorFlow, Transformers, FastAPI, Seaborn, LangChain, and LlamaIndex, Proficiency in integrating generative AI with enterprise applications using APIs, knowledge graphs, and orchestration tools, Hands-on experience with various vector databases (e. g. , PG Vector, Pinecone, Mongo Atlas, Neo4j) for efficient data storage and retrieval, Experience in dealing with large amounts of unstructured data and designing solutions for high-throughput processing, Hands-on experience deploying GenAI-based models to production environments, understanding and practical experience with MLOps principles, model evaluation, and establishing robust deployment pipelines, expertise in CI/CD principles and tools (e. g. , Jenkins, GitLab CI, Azure DevOps, ArgoCD) for automated builds, testing, and deployments, Proven experience with container orchestration platforms like OpenShift or Kubernetes for deploying, managing, and scaling containerized applications in a cloud-native environment
Nice to Have
Master’s degree preferred
What You'll Do.
Participate in establishment of new application systems
Implement new application systems
Coordinate with Technology team
Contribute to applications systems analysis
Contribute to programming activities
Build LLM-based applications
Tune LLM-based applications
Deploy LLM-based applications
Develop prompt engineering strategies
Create reusable prompt templates
Implement agentic framework use cases
Assess performance of GenAI features
Assess safety of GenAI features
Integrate generative AI with enterprise applications
Design solutions for high-throughput processing
Deploy GenAI-based models to production
Establish robust deployment pipelines
Deploy containerized applications
Manage containerized applications
Scale containerized applications
How You'll Work.
Team & Collaboration
working effectively with cross-functional teams
Full Job Description
The Applications Development Intermediate Programmer Analyst 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. **_Recommended Qualifications:_** * 4-8 years of relevant experience in Apps Development or systems analysis role * **Core AI/ML Foundations:** * Strong foundational knowledge in Machine Learning (ML modeling), Data Science, Statistics, and AI fundamentals, including Natural Language Processing (NLP), Neural Networks, and Large Language Models (LLMs). * **Generative AI & LLM Expertise:** * **Extensive hands-on experience** with leading LLMs such as Google Gemini, OpenAI models, Anthropic Claude, Mistral, Llama, and various other open-source LLMs. * **Critical:** Deep working knowledge and hands-on experience with Retrieval-Augmented Generation (RAG) pipelines, including advanced RAG techniques and their detailed implementation. * Proven ability to build, tune, and deploy LLM-based applications using platforms like Vertex AI, Hugging Face, etc. * Expertise in developing robust prompt engineering strategies, prompt tuning, and creating reusable prompt templates. * Hands-on experience with agentic framework-based use case implementation. * Working knowledge of Guardrails and methodologies for assessing the performance and safety of GenAI features. * **Programming & Data Engineering:** * Strong programming proficiency in Python, including extensive experience with libraries such as Pandas, NumPy, scikit-learn, PyTorch, TensorFlow, Transformers, FastAPI, Seaborn, LangChain, and LlamaIndex. * Proficiency in integrating generative AI with enterprise applications using APIs, knowledge graphs, and orchestration tools. * Hands-on experience with various vector databases (e.g., PG Vector, Pinecone, Mongo Atlas, N
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