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# Domain Lead | AI/ML

- **Company:** BuzzClan
- **Location:** Alpharetta, GA, United States
- **Experience:** Expert
- **Salary:** $80,000.0 - $102,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Software Quality, Computer Programming, Continuous Integration, Data Cleansing, Software Debugging, DevOps, Graph Database, Python (Programming Language), Knowledge Management, Neo4j, Performance Tuning, Tensorflow, Pytorch, Flask (Web Framework), Prompt Engineering, Generative AI, Fastapi, Containerization, Scikit Learn, Kubernetes, Machine Learning Operations, Restful APIs, Docker
- **Published:** July 3, 2026
- **Apply:** https://www.careerjet.com/jobad/us490e793253c5fcd03413cac57121bbef

## About the Role

Strong proficiency in Python (Fast API, Flask, async programming, RESTful APIs). Proven experience in AI/ML pipelines ? data preprocessing, model training, fine-tuning, and deployment (TensorFlow, PyTorch, Scikit-learn).
Must have hands-on with GenAI frameworks (LangChain, Llama Index, Lang Graph, Neo4j, Bedrock, etc.).
Hands-on experience implementing the RAG pipelines - Knowledge Management with vector databases, embeddings, Graphs. Working knowledge of prompt engineering, optimisation and fine-tuning.
Familiarity with Graph databases (Neo4j) or agent-based architectures.
Architect and code in Python for scalable, reusable, and high-performing systems.
Strong grounding in software quality engineering concepts and automation frameworks.
Solid understanding of CI/CD, containerization (Docker/Kubernetes), and cloud(AWS) deployment.
Excellent debugging, performance optimization, and solutioning skills.

## Description

Client is seeking an experienced Senior AI/ML & Generative AI Quality Engineer to join its Quality Engineering organization.
This role is responsible for validating and ensuring the quality, performance, reliability, and scalability of AI/ML and Generative AI applications.
The ideal candidate will possess strong expertise in Python, AI/ML pipelines, GenAI frameworks, RAG architectures, and cloud-native deployments while applying software quality engineering best practices across the AI development lifecycle.
The successful candidate will work closely with Data Scientists, AI Engineers, Product Owners, and DevOps teams to build robust testing strategies, automate AI validation processes, and ensure enterprise-grade AI solutions meet business, security, and compliance requirements.
Note- 10 years overall (minimum 5 years in AI/ML and GenAI)
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