AI Technical Support Engineer

Job Description Roles & Responsibilities About the Role: We are seeking a highly motivated AI Technical Support Engineer to support and maintain production AI/ML systems. This role is critical in ensuring the reliability, performance, and usability of AI-driven solutions by troubleshooting issues, supporting customers, and collaborating with engineering teams. You will work at the intersection of AI/ML, cloud infrastructure, and customer support , helping diagnose and resolve complex technical issues in real-world deployments Responsibilities Technical Support & Troubleshooting Investigate and resolve issues in AI/ML systems, including: Model inference errors Data pipeline failures API and integration issues Perform root cause analysis (RCA) and document findings Handle escalations and manage incidents within SLA targets AI/ML System Monitoring & Operations Monitor production systems for: Latency, accuracy, and error rates Diagnose model-related issues such as drift, degradation, or bias Support deployment and operation of AI models in cloud environments Customer & Stakeholder Support Provide technical guidance to customers and internal teams Assist developers with integrating AI APIs and services Communicate complex technical issues in a clear, actionable manner Deployment & MLOps Support Support CI/CD pipelines for ML workflows Assist with containerized deployments (Docker/Kubernetes) Work with cloud platforms (AWS, Azure, GCP) Documentation & Knowledge Management Develop and maintain: Troubleshooting runbooks Knowledge base articles FAQs and best practices Contribute to continuous improvement of support processes Cross-Functional Collaboration Partner with: Machine Learning Engineers DevOps and Cloud teams Product and Engineering teams Escalate product issues and influence long-term fixes Technical Skills Strong programming skills in Python Understanding of machine learning fundamentals : Model evaluation (precision/recall, accuracy) Training vs. inference workflows Experience with: APIs (REST/HTTP) SQL and data analysis tools (Pandas, NumPy) Familiarity with: Cloud platforms (AWS, Azure, or GCP) Containers (Docker, Kubernetes) Monitoring tools (Grafana, Prometheus, Datadog) Troubleshooting & Debugging Strong problem-solving skills with ability to: Analyze logs and system metrics Reproduce issues Identify root causes quickly Soft Skills Excellent communication skills (technical + non-technical audiences) Customer-focused mindset with strong ownership Ability to manage multiple priorities in a fast-paced environment Bachelor s degree in Computer Science, Data Science, AI, or related field. 2+ years of experience in technical support, software engineering, or ML systems. Preferred Qualifications Experience supporting production AI/ML systems Familiarity with MLOps tools (MLflow, Kubeflow, SageMaker) Experience with distributed systems troubleshooting Exposure to LLMs / Generative AI systems Key Performance Indicators (KPIs) Mean Time to Resolution (MTTR) SLA compliance Issue recurrence rate System uptime and reliability Customer satisfaction (CSAT) Nice-to-Have Knowledge of prompt engineering and LLM debugging Experience with vector databases or AI frameworks (LangChain, etc.) Background in AI safety, validation, or model monitoring Why Join Us Work on cutting-edge AI systems in production environments Collaborate with cross-functional engineering and product teams Opportunity to shape scalable AI support processes Desired Candidate Profile Bachelor s degree in Computer Science, Data Science, AI, or related field. 2+ years of experience in technical support, software engineering, or ML systems. Strong programming skills in Python Understanding of machine learning fundamentals : Model evaluation (precision/recall, accuracy) Training vs. inference workflows Experience with: APIs (REST/HTTP) SQL and data analysis tools (Pandas, NumPy) Familiarity with: Cloud platforms (AWS, Azure, or GCP) Containers (Docker, Kubernetes) Monitoring tools (Grafana, Prometheus, Datadog) Strong problem-solving skills with ability to: Analyze logs and system metrics Reproduce issues Identify root causes quickly Excellent communication skills (technical + non-technical audiences) Customer-focused mindset with strong ownership Ability to manage multiple priorities in a fast-paced environment Experience supporting production AI/ML systems Familiarity with MLOps tools (MLflow, Kubeflow, SageMaker) Experience with distributed systems troubleshooting Exposure to LLMs / Generative AI systems Knowledge of prompt engineering and LLM debugging Experience with vector databases or AI frameworks (LangChain, etc.) Background in AI safety, validation, or model monitoring Company Industry IT - Software Services Department / Functional Area IT Software Keywords AI Technical Support Engineer Get real-time job updates only on our App