ABOUT EGEN:

Egen is a fast-growing and entrepreneurial company with a data-first mindset. We bring together the best engineering talent working with the most advanced technology platforms, including Google Cloud and Salesforce, to help clients drive action and impact through data and insights. We are committed to being a place where the best people choose to work so they can apply their engineering and technology expertise to envision what is next for how data and platforms can change the world for the better. We are dedicated to learning, thrive on solving tough problems, and continually innovate to achieve fast, effective results. If this describes you, we want you on our team.
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ABOUT THE OPPORTUNITY:

We are seeking a AIOps Platform Engineer to design, implement, and scale intelligent observability solutions for our AIOps platform. This role blends deep expertise in machine learning, especially time series forecasting, anomaly detection, and event classification—with advanced cloud engineering skills to ensure robust, scalable, and secure deployments. The ideal candidate will integrate ML algorithms, GenAI components, and monitoring tools into a seamless operational ecosystem, enabling data-driven automation and actionable insights. You will work across the full stack of observability, from data ingestion and modeling to deployment and continuous optimization, ensuring the health, performance, and resilience of our platform.

BASIC QUALIFICATIONS:

• Hands-on experience with time series forecasting, anomaly detection, and event classification/correlation ML algorithms.
• Strong programming skills in Python (and optionally R) for modeling, automation, and cloud API interaction.
• Proficiency with ML frameworks such as TensorFlow, PyTorch, and scikit-learn.
• Deep understanding of Google Cloud and Azure services for ML deployment, observability, and infrastructure scalability.
• Knowledge of observability platforms including Prometheus, Grafana, Elasticsearch, Datadog, along with database technologies (MySQL, MongoDB, PostgreSQL).
• Experience with Git and other version control systems.
• Familiarity with MLOps practices, GenAI tooling, and modern code-assist solutions.
• Knowledge of testing frameworks and agile development methodologies.

RESPONSIBILITIES:

• Design, develop, and deploy ML algorithms and GenAI integrations for observability data in AIOps.
• Integrate LLM-based solutions, including prompt engineering, fine-tuning, and retrieval-augmented generation, for effective summarization.
• Integrate monitoring and observability tools within a cloud ecosystem.
• Deploy and scale ML solutions using Google Cloud and Azure services for observability and infrastructure scalability.
• Implement and maintain observability data storage solutions using Prometheus, Grafana, Elasticsearch, and relational/non-relational databases (e.g., MySQL, MongoDB, PostgreSQL).
• Apply testing frameworks and agile development methodologies to both ML and cloud-based components.
• Collaborate across engineering teams to ensure AI/ML outputs are effectively operationalized within the observability platform.

This role is eligible for our competitive salary and comprehensive benefits package to support your well-being:

• Comprehensive Health Insurance
• Paid Leave (Vacation/PTO)
• Paid Holidays
• Sick Leave
• Parental Leave
• Bereavement Leave
• 401 (k) Employer Match
• Employee Referral Bonuse