Engineer-Artificial Intelligence (AI)

In this role, you will design and develop Artificial Intelligence models and algorithms to solve Telecom network and business problems. You will work closely with engineering, operations, and site reliability engineering (SRE) teams to ensure seamless integration of Artificial Intelligence into workflows and deliver measurable value across the organization. Additionally, you will partner with engineering and delivery teams to embed Artificial Intelligence solutions into existing systems and processes, driving continuous innovation and operational efficiency. If you have a flair for Artificial Intelligence and a passion for solving complex problems, this role is for you. You have: An Engineering degree in Computer Science or equivalent (specialization in artificial intelligence will be a plus) with 4+ years of experience in AI, machine learning, or data science . Exposure to Telecom, cloud, or network engineering is a plus. Practical experience in Python, TensorFlow or PyTorch, LangChain, Hugging Face, and vector databases. It would be nice if you also had: Experience with cloud platforms like AWS, Azure, or Google Cloud, OpenShift/ Kubernetes/Helm, and MLOps tools. Familiarity with big data technologies such as Hadoop or Spark. Knowledge of natural language processing (NLP) and computer vision. Understanding of Telecom networks (5G, 4G, SDN, NFV, OSS/BSS), DevOps, and automation will be a plus. Design and develop artificial intelligence models and algorithms to address Telecom network and business challenges. Integrate Artificial Intelligence solutions into existing systems by partnering with engineering and delivery teams. Leverage large language models (LLMs), multi-agent systems, and automation to enhance network operations, including self-healing and incident response. Perform research and apply the latest Artificial Intelligence advancements to improve model performance and network resilience. Analyze complex data to generate insights for network planning, service management, and automation. Document methodologies and spread knowledge to drive ongoing innovation and partnership.