AI/ML Expert Agentic AI Solutions

Job description

As a AI/ML Expert Agentic AI Solutions, we are seeking a talented and ambitious individual to take on this role. In this position, you will have a significant impact on our organizations success by leading the architecture and development of cutting-edge AI/ML solutions for optical networks. Your work will directly contribute to enhancing network performance, optimizing operations, and strengthening our companys technological edge. HOW YOU WILL CONTRIBUTE AND WHAT YOU WILL LEARN • Design, develop, and optimize agentic AI solutions for a variety of business and customer use cases. • Transform existing processes and automation tools into intelligent, autonomous, and semi-autonomous workflows. • Define and implement solution architectures for agent orchestration, memory management, tool integration, guardrails, and human-in-the-loop workflows. • Enhance process efficiency, user experience, and operational scalability through AI-driven automation solutions. • Document solution designs, technical decisions, best practices, and implementation guidelines to support scalable delivery and maintenance. Qualifications You have: • Bachelors degree with 812 years of experience in AI/ML engineering and solution development. • Strong experience in AI/ML engineering, solution architecture, and end-to-end AI solution delivery. • Deep understanding of RAG, prompt engineering, vector databases, embeddings, and model evaluation techniques. • Hands-on experience with LLMs, generative AI technologies, and agentic AI frameworks for building intelligent applications and orchestration workflows. • Strong knowledge of software engineering best practices, including APIs, automation platforms, version control, testing, CI/CD, deployment, and responsible AI principles related to governance, security, and privacy. It would be nice if you also had: • Knowledge of cloud platforms, preferably Google Cloud Platform (GCP). • Experience with multi-agent systems, planning frameworks, reinforcement learning, and human-in-the-loop workflows. • Basic understanding of optical networking, IP networking, and transport technologies. • Familiarity with data engineering, knowledge graphs, and semantic search architectures.