Senior Ai Engineer

Your tasks

• Assess AI systems, machine learning models, and AI-powered applications against predefined benchmarks, performance thresholds, and responsible AI standards.
• Evaluate AI systems for fairness, transparency, accountability, reliability, privacy, security, and potential ethical risks.
• Design and implement technical mitigation strategies to address AI-related risks, including algorithmic bias, inaccurate outputs, model drift, and unintended system.
• Develop and maintain responsible AI assessment frameworks, evaluation methodologies, testing procedures, and monitoring mechanisms.
• Conduct AI risk assessments and impact analyses to identify potential risks throughout the AI development and deployment lifecycle.
• Implement and validate responsible AI controls to ensure AI systems meet internal policies, applicable regulatory requirements, and ethical guidelines.
• Collaborate with AI engineers, data scientists, machine learning engineers, software developers, cybersecurity teams, and governance stakeholders.
• Establish measurable indicators, testing criteria, and performance metrics to monitor AI system reliability, fairness, robustness, and compliance.
• Investigate AI model failures, unexpected outputs, and potential ethical concerns, and recommend corrective actions and continuous improvements.
• Support the development of AI governance documentation, risk reports, technical assessments, and compliance evidence.
• Monitor emerging responsible AI technologies, regulatory developments, industry standards, and best practices to improve AI governance and risk mitigation.
• Contribute technical recommendations and solutions to strengthen responsible AI implementation across enterprise AI initiatives, particularly in telecommunications environments.

Requirements

• Minimum Bachelor's degree in Computer Science, Artificial Intelligence, Data Science, Information Technology, Software Engineering, or a related technical field.
• Minimum 5 years of relevant professional experience in AI engineering, machine learning, responsible AI, AI governance, model risk management, or a similar role.
• Experience assessing AI systems against predefined benchmarks, evaluation criteria, and responsible AI standards.
• Strong understanding of responsible AI principles, including fairness, transparency, explainability, accountability, privacy, safety, and reliability.
• Hands-on experience designing and implementing technical controls or mitigation strategies for AI-related risks.
• Knowledge of AI model evaluation, bias detection, robustness testing, model validation, and performance monitoring.
• Understanding of machine learning algorithms, AI model development, and the AI lifecycle from development to deployment and monitoring.
• Ability to translate ethical AI principles, risk assessment findings, and governance requirements into practical technical solutions.

Mandatory / Core Skills

1. Responsible AI & AI Ethics: Understanding of responsible AI principles, ethical AI practices, fairness, transparency, explainability, and accountability.
2. AI Risk Assessment & Model Evaluation: Experience evaluating AI systems against defined benchmarks, performance thresholds, and risk criteria.
3. AI Risk Mitigation: Ability to design, implement, and validate technical controls to mitigate bias, reliability issues, and other AI-related risks.
4. Machine Learning & AI Systems: Strong understanding of AI/ML models, model validation, testing, and monitoring.
5. AI Governance & Compliance: Knowledge of AI governance frameworks, responsible AI policies, and applicable regulatory requirements.

Preferred / Good-to-Have Skills

• Experience working in the telecommunications industry.
• Familiarity with responsible AI frameworks and standards, such as NIST AI Risk Management Framework (AI RMF), ISO/IEC 42001, and ISO/IEC 23894.
• Experience with explainable AI (XAI), algorithmic fairness, bias detection, and model interpretability.

Skills: Machine Learning, IT Infrastructure Management, Gpu Server, Nvidia CUDA, Server Testing, Cdcp, Artificial Intelligence