Domain Lead | AI/ML

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) Quality Engineering Experience: 8, Job Category: Field Engineering/Audit & Inspections Degree Level: Bachelor’s Degree Job Description: Lead Auditor - GMP Quality Audits will perform high level assessments of …

• 1 day ago + *

IT Senior Auditor Global Payments

• Alpharetta, GA Every day, Global Payments makes it possible for millions of people to move money between buyers and sellers using our payments solutions for credit, debit, prepaid and merchant se…

• 1 month ago

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.