Provide front-line technical support: Diagnose and resolve production issues related to our generative AI applications, including performance bottlenecks, API errors, data inconsistencies, and infrastructure problems.
Monitor application health: Utilize monitoring tools and dashboards to track key metrics, identify anomalies, and proactively address potential issues before they impact users.
Incident Management: Follow established incident management procedures to document, escalate, and resolve production incidents, ensuring timely communication with stakeholders.
Collaborate with engineering teams: Work closely with development and infrastructure teams to identify the root cause of issues, implement fixes, and prevent future occurrences.
Develop and maintain documentation: Create and update technical documentation, including runbooks, knowledge base articles, and troubleshooting guides.
Automate support tasks: Identify opportunities to automate repetitive tasks and improve support efficiency through scripting and tooling.
Participate in on-call rotation: Provide on-call support on a rotational basis to ensure 24/7 coverage for critical applications.
Continuous Improvement: Contribute to the continuous improvement of our support processes and tools by identifying areas for optimization and implementing best practices.
Qualifications:
Bachelor's degree in Computer Science, Engineering, or a related field.
8-13 years of experience in application production support or a related role.
Strong understanding of software development lifecycle and DevOps principles.
Experience supporting cloud-based applications, preferably on AWS, Azure, or GCP.
Proficiency in at least one scripting language (e.g., Python, Bash).
Familiarity with monitoring tools (e.g., Datadog, Prometheus, Grafana).
Excellent problem-solving and analytical skills.
Strong communication and collaboration skills.
A passion for AI and machine learning.
Bonus Points:
Experience with generative AI models and algorithms (e.g., GANs, VAEs, Transformers).
Knowledge of MLOps principles and practices.
Experience with containerization technologies (e.g., Docker, Kubernetes).
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Technology
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Applications Support
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Full time
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Please see the requirements listed above.
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For complementary skills, please see above and/or contact the recruiter.
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