AI Operations Engineer

• Develop AI driven monitoring and analytics: Build, train and maintain machine learning models that analyze operational data (logs, metrics, events and traces) to detect anomalies, pinpoint root causes and predict incidents Configure AI agents that detect problems, understand context and execute remediation steps autonomously.
• Integrate AIOps tools with cloud and enterprise systems: Work with DevOps and SRE teams to integrate AIOps platforms into continuous integration/continuous delivery (CI/CD) pipelines and cloud infrastructure Leverage APIs to connect AI monitoring services to enterprise systems such as IT service management platforms and configuration management databases.
• Evaluate and deploy AIOps platforms: Assist in evaluating, implementing and tuning commercial AIOps tools (e.g., Moogsoft, Dynatrace, Splunk, BigPanda, Datadog) Configure agentic features in these platforms to enable automatic root cause analysis and remediation.
• Collaborate with cross functional teams: Partner with developers, operations staff and cybersecurity teams to ensure AI Ops integrations align with business goals Explain AIdriven insights and recommend improvements to stakeholders.
• Stay current on emerging technologies: Follow developments in agentic AI frameworks, generative AI, machine learning operations and observability. Continuously learn and experiment with new tools to improve system efficiency and reliability

• Education: Some college coursework in computer science, data science, information systems or a related field. Candidates without a degree should have an equivalent combination of training and experience.
• Experience: 1–2 years of hands-on experience in DevOps, site reliability or IT operations roles that used agentic AI or AIOps tools. Experience may include internships or co-ops.
• Technical skills:
  • Proficiency in Python or another scripting language for automating tasks and interacting with APIs
  • Understanding of machine learning concepts and frameworks (PyTorch)
  • Familiarity with observability stacks such as Prometheus, Grafana and ELK/OpenTelemetry, and basic knowledge of data visualization
  • Exposure to public cloud platforms (AWS) and infrastructure as code tools (Terraform, Ansible)
  • Ability to interpret telemetry data and spot trends; comfortable working with charts, logs and metrics.
• Soft skills: Strong problem-solving and analytical thinking, with the ability to troubleshoot issues and implement solutions. Excellent communication and collaboration skills to work with cross functional teams

• Handson experience with commercial AIOps platforms or building machine learning based incident response systems.
• Knowledge of Kubernetes, container orchestration and service mesh architecture.
• Background in log analysis, timeseries forecasting or unsupervised anomaly detection.
• Familiarity with IT service management (ITSM) processes and how they integrate with AIdriven operations
• Exposure to agentic AI frameworks (e.g., LangChain/LangGraph) or generative AI pipelines, particularly for RAG or LLM‑based chatops.

• Curiosity and continuous learning: AIOps is a rapidly evolving field. Candidates should be eager to explore new agentic AI techniques and stay up to date with emerging tools and frameworks
• Critical thinking: AI agents provide insights but still require human judgment; the engineer should be able to interpret AI recommendations, make strategic decisions and adjust guardrails as needed
• Team player: Success in AI Ops depends on collaboration. The candidate should be comfortable working with developers, SREs, data scientists and security teams to integrate AI capabilities into existing processes
• Attention to detail: Observability and AI pipelines handle large volumes of data; meticulous attention ensures data quality and accurate analysis

• Personalized Time Off: Take time when it’s needed most — whether that’s a family vacation, a reset day, or simply time to rest and refocus.
• Paid Sick Time: Separate, dedicated sick leave to care for yourself or loved ones.
• Volunteer Time Off: Paid time to give back and support causes that matter to you.
• Ten Paid Holidays: Enjoy meaningful moments and traditions throughout the year.
• Our Philosophy: We believe time away from work helps you bring your best self to it.

• World-Class Learning Access: Explore thousands of on-demand courses through platforms like LinkedIn Learning.
• Leadership & Technical Skill Building: Develop new capabilities and chart your own professional path.
• AI Empowerment: Use OpenAI tools to build fluency with emerging technology and harness AI as a creative partner for innovation and problem-solving.
• Tuition Reimbursement: Invest in formal education to advance your skills and career.
• Ongoing Learning Culture: Participate in company-led webinars on AI, inclusion, and industry trends—designed to inspire curiosity and continuous improvement.

• Wellness Initiatives: Company-sponsored programs that support physical, mental, and emotional well-being.
• Employee Assistance Program (EAP): Confidential support for you and your family’s needs.
• Comprehensive Benefits: Health and financial benefits that support your happiness and future.
• A Culture That Cares: At Frontline Education, we want every team member to learn, grow, and thrive—personally, professionally, and purposefully