Serve as the technical authority and hands-on leader in designing, building, and scaling next-generation Agentic AI solutions for autonomous network operations.
Be instrumental in the technical implementation of the core "AI brain" framework, working across the five-layer architecture of autonomous agents designed for continuous coverage: detection, aggregation, synthesis, investigation, and recommendation.
Drive the core technical efforts in Agentic Workflow Orchestration, including designing robust agent-to-agent communication patterns and structuring the overall task flow.
Lead the engineering and optimization of Large Language Model (LLM) components through advanced Prompt Engineering, Fine-tuning, and Context Engineering (RAG pipelines).
Design and deliver high-precision Retrieval Augmented Generation (RAG) systems using vector databases and semantic search to ground models in enterprise data.

Bachelor’s degree or four or more year of work experience.
Six or more years or relevant work experience.
Six or more years of experience in practicing data science or AI engineering in a business environment, focusing on applying AI/ML, GenAI, and Agentic frameworks.
Deep technical mastery of Prompt Engineering, Context Engineering, and building Agents Skills & Tools.
Expertise in distributed computing systems and strong coding proficiency in Python and Spark.
Proven AI Hygiene experience by designing and deploying end-to-end MLOps and LLM Ops pipelines, including versioning, real-time monitoring, and continuous integration/continuous deployment (CI/CD).
Experience with deep learning, Natural Language Processing (NLP), and Foundation Model architectures (LLM/SLM).

Principal Engineer – AI Science

Key skills