AI Engineer

Inherent Technologies - Dallas, TX

Full-time - Mid Level

Dallas, TX

Professional, Scientific, and Technical Services

About the position

The AI Engineer will be responsible for developing, optimizing, and monitoring AI-driven solutions within a telecom-focused environment. This role involves implementing systems like OpsGPT and Avertack GPT to enhance operational efficiency through various AI techniques, including prompt engineering, visualization, and LLM tuning.

Responsibilities

• Design and develop a functional chatbot for telecom-related operational queries.
• Define and implement conversation flows, response templates, and troubleshooting actions.
• Collaborate with data teams to integrate relevant data sources for accurate responses.
• Experiment with prompt structures to improve response accuracy and efficiency.
• Conduct A/B testing on prompt formats and optimize based on feedback.
• Document and maintain prompt design guidelines for optimization practices.
• Identify and design use cases for Avertack GPT in telecom operations.
• Translate business needs into actionable AI solutions and workflows.
• Prototype workflows for each use case to align with business objectives.
• Build visualizations using charts and dashboards to track key metrics.
• Enable filtering and drill-down features for detailed analysis of system performance.
• Implement comprehensive monitoring for Avertack GPT transactions.
• Set up alerting for anomalies or threshold breaches in performance metrics.
• Research ontology applications and define core entities for telecom operations.
• Fine-tune LLM on domain-specific telecom data for improved accuracy.

Requirements

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related field.
• 3-5 years in AI engineering, machine learning, or a similar role, preferably in a telecom environment.
• Proficiency in Python for AI and ML development.
• Strong experience with ML frameworks such as TensorFlow, PyTorch, and Scikit-Learn.
• Practical experience with NLP tools and prompt optimization techniques.
• Experience with visualization tools (e.g., Kibana, Power BI) and charting libraries (e.g., Matplotlib, Seaborn).
• Familiarity with big data platforms (e.g., Apache Spark) and Graph DBs (e.g., Neo4j).
• Proficiency in using monitoring tools to track performance metrics.
• Strong problem-solving and analytical skills.
• Ability to collaborate effectively with technical and non-technical stakeholders.

Nice-to-haves

• Understanding of telecom-specific data formats and industry protocols.
• Experience with optimization algorithms for network performance enhancement.
• Relevant certifications such as AWS Certified Machine Learning or Google Professional Machine Learning Engineer.