Python Jobs in Dallas, TX

Job Description

• It is a 100% Onsite position in Dallas, TX.
  
• Local Candidates preffered.
  

• Focus on building AI-driven solutions using Python, including LLMs, embeddings, knowledge graphs, and RAG architectures..
  
• Eligible Hacker Rank assessment.
  

• Build GenAI applications leveraging foundation models and advanced architectures such as GraphRAG.
  
• Develop autonomous AI agents using modern agentic frameworks.
  
• Design and deploy RAG and GenAI services using Python (FastAPI), Docker, and cloud platforms (AWS, Azure, or GCP).
  
• Build scalable REST APIs that power LLM-driven applications integrated with enterprise data sources.
  
• Implement LLM evaluation frameworks using tools such as Ragas, LangSmith, or custom benchmarks to measure answer relevance, groundedness, and hallucination rates.
  
• Apply LLMOps/MLOps practices, including CI/CD pipelines, prompt/version management, automated testing, and monitoring of latency, cost, and response quality.
  
• Develop systems leveraging embeddings at scale, knowledge graphs, and ontology extraction.
  
• Collaborate across engineering teams, mentor developers, and help drive innovation in GraphRAG and agentic AI architectures.
  

Requirements

• Degree in Computer Science, AI/ML, or related field.
  
• 5+ years of AI/ML-focused software engineering experience.
  
• Production experience building LLM-based or agentic AI systems.
  
• Strong expertise in Python and modern AI frameworks.
  
• Experience with embeddings, knowledge graphs, ontology extraction, and advanced RAG/GraphRAG implementations.
  
• Full-stack development experience (Python back end + modern front end).
  
• Experience deploying AI workloads to AWS, Azure, or GCP.
  
• Familiarity with LLMOps/MLOps tooling and model evaluation frameworks.
  
• Strong problem-solving, communication, and collaboration skills.
  

Requirements
Degree in Computer Science, AI/ML, or related field. 5+ years of AI/ML-focused software engineering experience. Production experience building LLM-based or agentic AI systems. Strong expertise in Python and modern AI frameworks. Experience with embeddings, knowledge graphs, ontology extraction, and advanced RAG/GraphRAG implementations. Full-stack development experience (Python back end + modern front end). Experience deploying AI workloads to AWS, Azure, or GCP. Familiarity with LLMOps/MLOps tooling and model evaluation frameworks. Strong problem-solving, communication, and collaboration skills.