What are the responsibilities and job description for the Python Developer RAG / GenAI Engineer position at Bramkas Inc.?
Python Developer – RAG / GenAI Engineer
- Location: Dallas, TX (Onsite /Hynrid ) or Remote (US)
- Employment Type: Full-Time
- Experience: 5 Years Experience
- Skills : GEN AI , RAG , Python
We are actively hiring for a Python Developer with strong experience in RAG (Retrieval Augmented Generation) and GenAI-based systems to build intelligent, scalable AI applications.
This role is focused on designing and implementing document-driven AI systems, real-time data pipelines, and LLM-powered solutions.
Role Overview
We are looking for a hands-on engineer who can build end-to-end GenAI pipelines — from document ingestion to retrieval and response generation.
You will work on modern AI architectures involving vector databases, embeddings, and real-time LLM integrations, helping deliver production-grade intelligent systems.
Key Responsibilities
- Build and maintain applications using Python for AI/GenAI use cases
- Design and implement RAG-based architectures for document retrieval and response generation
- Develop document ingestion pipelines:
- Loading → Parsing → Chunking → Embedding → Storage
- Work with vector databases for similarity search and indexing
- Implement document citation / source attribution in LLM responses
- Integrate with LLM providers (OpenAI, AWS Bedrock, etc.)
- Develop real-time systems using Streaming APIs and Server-Sent Events (SSE)
- Handle metadata management, indexing, and retrieval optimization
- Work with agent-based systems and integration patterns (MCP or similar)
- Collaborate with product, UI, and backend teams for full solution delivery
Required Skills
- Strong hands-on experience in Python development
- Proven experience building RAG (Retrieval Augmented Generation) systems
- Experience with Vector Databases:
- Embeddings, similarity search, indexing
- Strong experience in:
- Document parsing & extraction (PDF, structured/unstructured data)
- Document ingestion pipelines
- Experience with:
- Streaming APIs and SSE (Server-Sent Events)
- LLM integrations (OpenAI, Bedrock, etc.)
- Understanding of:
- MCP (Model Context Protocol) or similar agent frameworks
- Strong knowledge of data handling, metadata, and retrieval optimization
Good to Have
- Experience with LangChain / LangGraph or similar frameworks
- Experience with chat-based or agent-based UI integrations
- Exposure to real-time AI applications and conversational systems
What We’re Looking For
- Strong problem-solving mindset with hands-on coding ability
- Experience building production-grade AI systems (not just POCs)
- Ability to work independently in a fast-paced environment
- Passion for working with modern AI / GenAI technologies
Why Join
- Work on cutting-edge GenAI and RAG architectures
- Opportunity to build real-world AI products at scale
- Flexible work options (Dallas onsite or remote)
- Collaborative and innovation-driven environment