Senior Data Scientist – Gen AI Engineer - Assistant Vice President

CITI
Department Icon Data Science Analytics & Machine Learning
149+ Applicants
Posted: 2 weeks ago
8-12 years
Pune, Maharashtra
work from office
Posted: 2 weeks ago
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Applicants: 149+
Job Description
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Job Description

Minimum Qualifications
  • Bachelors degree in Computer Science, Data Science, Artificial Intelligence, or a related quantitative field.
  • 8–12 years of experience as a Data Scientist or equivalent role, with at least 2 years of specialized, hands-on experience in Generative AI, including leading technical development and mentoring teams.
  • Demonstrable experience across the full lifecycle of production-level GenAI projects — from ideation and prototyping through deployment, monitoring, and ongoing maintenance in live environments. Proof-of-concept work alone is insufficient.
Core Responsibilities
  • Working with financial and enterprise data, applying modern NLP and GenAI techniques to solve business problems.
  • Designing, refining, and systematizing prompt engineering strategies for large language models (LLMs), including structured prompting, chain-of-thought, and few-shot/zero-shot approaches.
  • Collaborating with business stakeholders to translate requirements into GenAI-powered solutions.
  • Developing, testing, and maintaining production-grade Python code for GenAI applications.
  • Integrating with vector databases (e.g., Pinecone, Weaviate, Milvus, pgvector, Qdrant) for retrieval-augmented generation (RAG) pipelines.
  • Building, monitoring, and optimizing MLOps/LLMOps pipelines for continuous model deployment and observability.
  • Researching and evaluating emerging GenAI technologies, frameworks, and best practices to maintain competitive advantage.
  • Troubleshooting and debugging GenAI models and agentic systems in production, including rapid identification and resolution of issues in real-world deployments.
  • Communicating complex AI/ML concepts clearly to non-technical stakeholders, translating technical jargon into actionable business terms.
  • Participating in and leading team meetings, design reviews, and architecture discussions.
Technical Skills
Programming & Foundations
  • Expert-level Python proficiency, including:
    • Core Python: data structures (lists, dictionaries, sets), algorithms, object-oriented programming, async programming, file handling, and exception handling.
    • Scientific computing: NumPy, Pandas, SciPy.
    Machine Learning
    • Scikit-learn, XGBoost, LightGBM.
    • Strong understanding of advanced modeling techniques, model evaluation, hyperparameter tuning, and deployment strategies.
    Deep Learning
    • PyTorch (preferred/primary), TensorFlow/Keras.
    • Familiarity with training, fine-tuning, and inference optimization for neural network architectures.
    Generative AI (Updated for Current Landscape)
    Area
    Key Technologies & Concepts
    LLM Frameworks:
    Hugging Face Transformers, LangChain,
    Free Workshop
    LlamaIndex    , Semantic Kernel
    Agentic AI:
    LangGraph, CrewAI, AutoGen, tool-use/function-calling patterns, multi-agent orchestration
    LLM Architectures:
    Transformer architectures (decoder-only, encoder-decoder), Mixture-of-Experts (MoE), multimodal models (vision-language models)
    RAG (Retrieval-Augmented Generation):
    Advanced RAG patterns (hybrid search, re-ranking, query decomposition, contextual retrieval), chunking strategies, embedding models (e.g., OpenAI, Cohere, open-source sentence-transformers)
    Vector Databases
    Pinecone, Weaviate, Milvus, Qdrant, pgvector, ChromaDB
    Prompt Engineering:
    Structured prompting, chain-of-thought, ReAct, few-shot/zero-shot, prompt chaining, guardrails and output parsing
    Model Serving & Optimization
    vLLM, TGI (Text Generation Inference), ONNX Runtime, quantization (GPTQ, AWQ, GGUF), model distillation
    Evaluation & Observability
    LLM evaluation frameworks (RAGAS, DeepEval, custom evals), LLM observability tools (LangSmith, Arize Phoenix, Weights & Biases), red-teaming and safety testing
    API Development
    FastAPI, RESTful and streaming API design for GenAI applications, WebSocket integration
    Responsible AI
    Bias detection and mitigation, content safety filters, hallucination reduction techniques, AI governance frameworks
    MLOps / LLMOps
    • CI/CD for ML/GenAI pipelines (e.g., GitHub Actions, GitLab CI).
    • Experiment tracking and model registry (MLflow, Weights & Biases).
    • Containerization and orchestration: Docker, Kubernetes.
    • Infrastructure-as-code and deployment automation.
    Cloud Platforms
    • Proficiency in at least one major cloud platforms AI/ML services:
      • AWS (Bedrock, SageMaker, Lambda)
      • Azure (Azure OpenAI Service, Azure AI Studio, Azure ML)
      • GCP (Vertex AI, Gemini API)
      Soft Skills

      Looking to get Placed? Try our Placement Guarantee Plan


      • Excellent communication and collaboration skills — both written and verbal — with the ability to effectively convey technical concepts to diverse audiences, including senior leadership and business partners.
      • Ability to articulate the challenges, trade-offs, and successes of deploying GenAI solutions at scale.
      • Proactive approach to continuous learning in the rapidly evolving GenAI landscape.
      Preferred Qualifications
      • Masters or Ph.D. in a relevant field (Computer Science, AI/ML, NLP, or related).
      • Experience with MLOps/LLMOps and building robust, automated AI pipelines at enterprise scale.
      • Deep understanding of cloud-native architectures and their application in GenAI workloads.
      • Experience developing and deploying conversational AI and agentic AI solutions in production environments.
      • Contributions to open-source projects, research, or publications in the field of Generative AI or NLP.
      • Experience building, curating, and managing large-scale datasets for training or fine-tuning GenAI models.
      • Familiarity with graph databases (e.g., Neo4j) and knowledge graph integration with LLMs (GraphRAG).
      • Experience with multimodal AI (text, image, audio, video).
      Education
      • Bachelors degree / University degree or equivalent experience.
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      Job Family Group:
      Technology
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      Job Family:
      Applications Development
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      Time Type:
      Full time
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      Most Relevant Skills
      Please see the requirements listed above.
      ------------------------------------------------------
      Other Relevant Skills
      For complementary skills, please see above and/or contact the recruiter.
      ------------------------------------------------------
      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 Citis EEO Policy Statement and the Know Your Rights poster.

Skills

Artificial IntelligencePythonData ScienceDeep LearningMachine LearningAi/mlData ScientistPrompt EngineeringLarge Language ModelsAiMlAi Engineer

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About Company

CITI, or Citigroup Inc., is a leading global bank with a rich history of over two centuries. It offers a wide range of financial products and services, including banking, investments, and wealth management, serving millions of customers worldwide. CITI Careers present exciting opportunities for individuals seeking to build rewarding and impactful careers in finance. With a strong focus on innovation, diversity, and sustainability, CITI fosters a dynamic work environment where employees can thrive and grow professionally. Joining CITI means becoming part of a global team dedicated to driving progress and empowering clients to achieve their financial goals.

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Important dates & deadlines?

Application Deadline

01 Jul 26, 03:05 PM IST

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Senior Data Scientist – Gen AI Engineer - Assistant Vice President

CITI

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