AI/ML Expert – Agentic AI Solutions

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 organization’s 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 company’s technological edge.
You have:
Bachelor’s degree with 8–12 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.
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.

Work arrangement
Hybrid