Data Scientist with Python AI/ML

Title : Data Scientist with Python AI/ML

Location: Atlanta, GA (Inperson interview needed)

Position type: W2 contract.

Job Description

We are looking for a highly capable Technical Lead –Python & AI/ML with deep expertise in backend engineering, LLM-based applications, RAG architectures, and AI agent frameworks.

You will lead the design, development, and deployment of production-grade AI systems built on Python, modern LLM tooling, retrieval engines, embeddings, and vector databases.

This is a hands-on leadership role focused on building scalable and intelligent AI products.

Investment Banking and financial domain is needed.

Key Responsibilities

• Lead the architecture and development of LLM-driven applications, AI agents, and RAG-based systems.
• Provide technical guidance, conduct code reviews, and mentor junior team members.
• Drive best practices in Python backend engineering, API development, and AI system design.
  
  

Backend Engineering (Python)

• Build and maintain backend services using FastAPI or Flask.
• Develop scalable API endpoints for AI applications, embeddings, and retrieval systems.
• Ensure backend code quality, modularity, performance, and maintainability.
  
  

LLMs, RAG, and AI Agent Development

• Build AI applications using: LangChain, LangGraph, Semantic Kernel, Haystack, LlamaIndex, AutoGen
• Develop autonomous or semi-autonomous AI agents with tool calling and workflow graphs.
• Implement Retrieval-Augmented Generation (RAG), embedding pipelines, chunking strategies, reranking, and grounding techniques.
• Work with OpenAI SDK and other LLM providers (Anthropic, Azure OpenAI, Cohere, etc.).
• Manage prompt engineering, prompt routing, safety guardrails, and evaluation metrics.
  
  

Data & Vector Search Engineering

• Build data pipelines for indexing, embeddings, and retrieval workflows.
• Work with SQL databases (PostgreSQL, MySQL, etc.) for metadata and application storage.
• Work with vector databases such as: Redis, Postgres with pgvector, Elasticsearch, Neo4j, or others.
• Implement and optimize search workflows using FAISS or similar similarity search libraries.
  
  

MLOps, Deployment & Observability

• Deploy AI services using Docker, container orchestration, and cloud environments.
• Implement monitoring for AI behavior, performance, error rates, and retrieval accuracy.
• Set up CI/CD pipelines for backend and AI components.
• Optimize inference cost, latency, and reliability.
  
  

Cross-Functional Collaboration

• Collaborate with product, data engineering, and business teams to understand requirements.
• Translate business problems into scalable AI architectures and deliver practical solutions.
• Communicate technical decisions, trade-offs, and progress to stakeholders.
  
  

Required Qualifications

• Bachelor’s/Master’s degree in Computer Science, AI/ML, Data Science, or related fields.
• 10+ years of experience in Python backend development.
• Strong proficiency in FastAPI or Flask.
• Strong working knowledge of SQL databases (Postgres, MySQL, etc.).
• Hands-on expertise with vector databases:
  
  

Redis , Postgres/pgvector , Elasticsearch , or Neo4j .

• Practical experience with FAISS for similarity search.
• Hands-on experience with modern LLM frameworks:
  
  

LangChain, LangGraph, Semantic Kernel, Haystack, LlamaIndex, AutoGen .

• Strong understanding of:
• Embeddings & vector search
• RAG pipelines
• Retrieval optimization
• Chunking strategies
• Document loaders & indexing
• Experience building AI apps using OpenAI SDK or similar.
• Experience deploying APIs/services using Docker and cloud environments.
• Leadership experience: guiding teams, conducting reviews, driving architecture decisions.