Urgent Need :: Generative AI Engineer // Dallas, TX (Hybrid Role)

[Sai kumar Opsaway]

Hi All,

Position: Generative AI Engineer
Location: Dallas, TX (Hybrid Role)

Exp: 12+ minimum 

Job Description

We are seeking a highly skilled Generative AI Engineer / Data Scientist to join a strategic AI transformation initiative for the banking and financial services domain at Citibank through Wipro. The ideal candidate will have strong expertise in Large Language Models (LLMs), NLP, Machine Learning, Generative AI frameworks, and enterprise-scale AI solution development.

The candidate will work closely with business stakeholders, data engineers, architects, and product teams to design, develop, and deploy scalable AI-driven solutions focused on automation, intelligent search, conversational AI, document intelligence, risk analytics, and operational efficiency.

Required Skills

• Strong experience in Generative AI, Machine Learning, and NLP solutions
• Hands-on experience with LLMs such as GPT, Llama, Claude, Gemini, or Mistral
• Experience building RAG (Retrieval-Augmented Generation) pipelines
• Strong proficiency in Python
• Experience with AI/ML frameworks:
• LangChain
• LlamaIndex
• Hugging Face
• Transformers
• TensorFlow / PyTorch / Scikit-learn
• Strong experience with vector databases:
• Pinecone
• FAISS
• ChromaDB
• Weaviate
• Experience with prompt engineering and model optimization
• Hands-on experience with cloud platforms:
• AWS / Azure / GCP
• Experience working with structured and unstructured enterprise datasets
• Strong SQL and data analytics skills
• Experience deploying AI models into production environments
• Knowledge of REST APIs and microservices architecture
• Familiarity with MLOps concepts and CI/CD pipelines
• Experience with Docker and Kubernetes is preferred

Responsibilities

• Design and develop enterprise-grade Generative AI solutions for banking use cases
• Build intelligent chatbots, document summarization systems, semantic search, and AI assistants
• Develop scalable RAG pipelines integrating enterprise knowledge bases and vector search
• Fine-tune and optimize LLM-based applications for accuracy, latency, and cost efficiency
• Collaborate with business teams to identify AI-driven automation opportunities
• Build NLP pipelines for document processing, compliance analysis, and financial insights
• Develop reusable AI frameworks and prompt engineering standards
• Integrate AI applications with enterprise APIs, databases, and cloud services
• Perform model evaluation, tuning, monitoring, and governance
• Ensure compliance with enterprise security, governance, and regulatory standards
• Work closely with DevOps and Data Engineering teams for scalable AI deployment

Preferred Qualifications

• Banking or Financial Services domain experience
• Experience with:
• AML
• Fraud Analytics
• Risk & Compliance
• Treasury / Payments
• Customer Analytics
• Exposure to AI governance and responsible AI frameworks
• Experience with Databricks, Snowflake, or Spark
• Knowledge of Azure OpenAI or AWS Bedrock services

Education

• Bachelor’s or Master’s degree in Computer Science, Data Science, Artificial Intelligence, Statistics, or related field

Nice to Have

• Experience with autonomous AI agents
• Multi-agent orchestration frameworks
• Graph RAG implementations
• Real-time AI inference optimization
• AI observability and monitoring tools

Key Technologies

Python | Generative AI | LLM | LangChain | LlamaIndex | RAG | NLP | Hugging Face | OpenAI | Azure OpenAI | AWS Bedrock | Vector Databases | Pinecone | FAISS | Machine Learning | PyTorch | TensorFlow | Spark | Snowflake | Docker | Kubernetes | REST APIs | MLOps | CI/CD