Job Summary

Role: AI Operations Automation Specialist

Number of positions: 1

We are seeking a hands-on, highly technical AI Operations Automation Engineer with around 2+ years of experience to join our centralized AI Product Support Operations team. Reporting directly to the Senior AIOps Lead, you will serve as the hands-on technical builder responsible for executing automation pipelines, integrating intelligent tools, and building data-driven systems across our AI product ecosystem.

In this role, your primary mission is to write code, connect APIs, deploy RAG-driven knowledge tools, and build operational dashboards under the guidance of the Senior AIOps Lead. You will work closely with L1/L2 support teams to eliminate manual workflows, automate ticket triage, and build automated diagnostic mechanisms that drive down Mean Time to Resolution (MTTR).

Qualifications

- Education: Bachelor's or Master's degree in Computer Science, Information Technology, Software Engineering, or a related quantitative field.
- Experience: ~2 years of hands-on experience in Software Engineering, AIOps, DevOps, Systems Automation, or Technical Support Engineering.

Key Responsibilities

- Hands-On Automation AI Scripting
- Build, test, and deploy automated scripts (Python, Shell, or PowerShell) and API integrations under the direction of the Senior AIOps Lead to streamline operational processes.
- Develop and maintain RAG-based (Retrieval-Augmented Generation) search tools and LLM utilities that index historic tickets, logs, and root-cause analyses (RCAs) so L1/L2 engineers can instantaneously surface past fixes.
- Implement conversational AI bots, webhooks, and self-service automation workflows within our ticketing portals to auto-resolve routine Tier-1 inquiries.

- Operational Dashboards Diagnostics





- Construct and customize automated dashboards (e.g., ServiceNow) to provide real-time visual metrics on system uptime, ticket velocity, MTTR, SLA compliance, and CSAT.
- Implement automated log-scraping and context-enrichment scripts that pre-fetch relevant telemetry data and append it directly to incoming support tickets upon creation.

- L1/L2 Support Engineering Support

- Pair with L1/L2 support engineers to identify repetitive manual tasks, converting friction points into single-click scripts or auto-remediation triggers.
- Help structure log outputs and standardize ticket tags to ensure incident history remains clean, searchable, and machine-readable.

- AIOps System Monitoring Execution

- Assist the Senior AIOps Lead in configuring real-time alert triggers and predictive anomaly detection models across cloud infrastructure.
- Run automated stress-test scripts and assist with validating self-healing infrastructure routines for recurring platform errors.

Technical Essentials

- Scripting Coding: Solid proficiency in Python or Shell scripting for building micro-automation tasks, log parsing, and utility tooling.
- APIs Data Pipelines: Direct hands-on experience connecting REST APIs, webhooks, JSON parsers, and data ingestion workflows.
- AI/LLM Utilities: Practical experience using LLM APIs, vector databases, or basic RAG architectures for text/document search and classification.




- ITSM Visualization: Working knowledge of ITSM platforms (Jira Service Management, ServiceNow) alongside visualization platforms (Looker Studio).
- Cloud Environments: Base-level understanding of cloud infrastructure (AWS, Azure, or GCP), microservice architectures, and system telemetry logs.

Soft Skills Behavioral Attributes

- Builder Mentality: Relentless focus on solving operational bottlenecks with clean, maintainable code rather than temporary manual workarounds.
- Technical Agility: High adaptability to rapidly test, iterate, and refine scripts based on feedback from the Senior AIOps Lead and support engineers.
- Structured Problem Solving: Strong ability to trace software errors, read stack traces, and translate raw system logs into clear operational metrics.

Nice-to-Have / Added Advantages

- Prior exposure to LLM framework engineering (e.g., Lang Chain, Llama Index, or Anthropic APIs).
- Certifications: AWS/GCP Certified Developer/SysOps or Python certifications.
- Familiarity with SQL, vector search, or log management engines.

Success Metrics

- MTTR Reduction: Lowering resolution times through automated diagnostics and fast access to prior solution data for L1/L2 teams.
- Ticket Deflection Rate: Measurable percentage of Tier-1 issues resolved automatically via self-service and bot interventions.
- Dashboard Accuracy Coverage: Comprehensive, real-time visual tracking of all core metrics (Uptime, MTTR, CSAT, Ticket Trends).

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

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