Senior AI / GenAI Engineer ( F2F interview is required) ( Banking/Finance domain)
Type: Contract
Location: GA/ NY ( Hybrid 3 days)
Rate: DOE
Job Summary:
Candidates must have experience delivering enterprise AI solutions in production environments, NOT only POC or personal projects/Educational Projects .
We are seeking a Senior AI / GenAI Engineer with strong experience in machine learning, generative AI, and enterprise-scale AI platform development. The ideal candidate should have hands-on experience building production-grade AI systems, including Retrieval-Augmented Generation (RAG) platforms, vector search pipelines, autonomous AI agents, and scalable ML model deployment. The role requires expertise in Python-based ML development, LLM frameworks, vector databases, and AI orchestration frameworks such as LangChain, LangGraph, and Hugging Face.
Skill Matrix (Provide this for all profile submissions):
GenAI Engineer- Skill/Competency | Hands-on experience in years. Enter 0 if you have theoretical knowledge | Rating (1-10)
10 Highest
Python
RAG, Vector DB, Chunking, Embedding
Data Pre-Processing
Prompt Engineering
GenAI Models Familiarity
Framework & Libraries - LangChain, Hugging Face, Langgraph similar framework build autonomous loop
Azure Cloud Computing/OpenAI services
API Integration and Development
Gen AI solution built for enterprise solutions (Not POC, Educational, Personal)
Mandatory In-person interview in GA or NY - Enter Yes to confirm.
Key Responsibilities:
• Strong Python development experience (7+ years).
• Hands-on experience with RAG, Vector DB, Embeddings and document chunking, Semantic search pipelines
• Experience with LangChain, LangGraph, and Hugging Face.
• Experience with Pandas, NumPy, and data preprocessing pipelines.
• Experience deploying ML models as REST APIs and integrating AI with enterprise systems.
Required Skills & Qualifications:
• ** Mandatory In-person interview in GA or NY
• ** Experience with enterprise level projects only - No college, Educational, POC Projects
• Strong Python development experience (7+ years).
• Hands-on experience with RAG, Vector DB, Embeddings and document chunking, Semantic search pipelines
• Experience with LangChain, LangGraph, and Hugging Face.
• Experience with Pandas, NumPy, and data preprocessing pipelines.
• Experience deploying ML models as REST APIs and integrating AI with enterprise systems.
Preferred Qualifications:
• Experience with Natural Language Processing (NLP) and Deep Learning.
• Familiarity with Transformers and Large Language Models (LLMs).
• Experience with Cloud ML platforms such as Azure AI, AWS SageMaker etc
Nice to Have:
• Experience building AI agents or autonomous systems.
• Knowledge of vector databases (Pinecone, Weaviate, Milvus, FAISS).
• Experience with MLOps practices, Docker, and Kubernetes.
• Exposure to multimodal AI systems.