Cynet Systems · 1 week ago
Gen AI Architect (Eval Framework)
Cynet Systems is a company focused on advanced technology solutions, and they are seeking a Gen AI Architect to design and develop GenAI-based applications. The role involves implementing multi-agent frameworks, defining evaluation standards, and optimizing models for business impact while engaging with stakeholders to align solutions with strategic goals.
EmploymentRecruitingStaffing Agency
Responsibilities
Design and develop GenAI-based applications using advanced techniques such as Retrieval-Augmented Generation (RAG), text-to-SQL, function calling, and agentic architectures
Implement multi-agent frameworks and explore graph-based GenAI approaches (e.g., GraphRAG) for complex problem-solving
Define and enforce evaluation standards and best practices for GenAI agents, RAG pipelines, and multi-agent orchestration
Performance evaluations to optimize ML and GenAI models for accuracy, scalability, and business impact
Engage with business stakeholders to understand requirements, gather feedback, and tailor solutions to meet strategic goals
Translate business needs into technical specifications and actionable plans
Ensure adherence to software engineering best practices, including version control (Git), CI/CD pipelines, documentation, and unit testing
Stay current with emerging GenAI evaluation tools, frameworks, and methodologies
Provide technical leadership and mentor team members on best practices and emerging GenAI technologies
Qualification
Required
Sound experience with Retrieval-Augmented Generation (RAG), fine-tuning, and multi-agent orchestration
Experienced in developing GenAI applications leveraging multi-agent frameworks and/or graph-based GenAI approaches (e.g., GraphRAG)
Proficient in using common NLP and/or ML Python frameworks, such as PyTorch, TensorFlow, Transformers/Hugging Face, and NumPy
LLM skills including fine-tuning, LLMOps, function-calling, and retrieval augmented generation (RAG)
Familiarity with data governance, AI ethics, and responsible AI practices
Strong proficiency in Python
Experience following software best practices in team settings, including version control (Git), CI/CD, documentation, & unit testing
Exposure to Microsoft Azure or similar cloud computing ecosystem
Ability to design scalable solutions and optimize performance for business impact
Strong problem-solving skills and the ability to work in a fast-paced, dynamic environment
Familiarity with vector databases, RAG pipelines, and agentic frameworks
Excellent communication and documentation skills
Preferred
Advanced GenAI Expertise: Experience developing applications using multi-agent frameworks and/or graph-based approaches such as GraphRAG and LangGraph
Cloud & MLOps Proficiency: Hands-on experience with Azure AI services, containerization (Docker/Kubernetes), and ML pipelines