AIOps SME

Company Description

About Sutherland: 

Artificial Intelligence. Automation. Cloud engineering. Advanced analytics. For business leaders, these are key factors of success. For us, they’re our core expertise.

We work with iconic brands worldwide. We bring them a unique value proposition through market-leading technology and business process excellence.

We’ve created over 200 unique inventions under several patents across AI and other critical technologies. Leveraging our advanced products and platforms, we drive digital transformation, optimize critical business operations, reinvent experiences, and pioneer new solutions, all provided through a seamless “as a service” model.

For each company, we provide new keys for their businesses, the people they work with, and the customers they serve. We tailor proven and rapid formulas, to fit their unique DNA. We bring together human expertise and artificial intelligence to develop digital chemistry. This unlocks new possibilities, transformative outcomes and enduring relationships.

Sutherland

Unlocking digital performance. Delivering measurable results

Job Description

AIOps Architect to lead the design and implementation of an AI-based observability and correlation engine using Selector AI. Architect solutions that enhance system reliability, automate incident management, and enable proactive IT operations through advanced machine learning (ML) and event correlation.

Key Responsibilities

• Design & Implementation: Architect and deploy AI-driven observability platforms using Selector AI to unify metrics, logs, traces, and events across hybrid cloud environments.
• AI/ML Integration: Develop correlation engines to identify patterns, reduce noise, and automate root cause analysis (RCA) using ML models.
• Tooling & Automation: Integrate Selector AI with existing monitoring tools (e.g., Prometheus, Grafana, ELK, New Relic, Dynatrace) and orchestrate automated remediation workflows.
• Model Development: Build and train ML models for anomaly detection, predictive alerting, and incident prioritization.
• Collaboration: Partner with DevOps, SRE, and Selector Data science teams to align AIOps strategies with business goals.
• Performance Optimization: Continuously refining correlation rules, reduce false positives, and improve system accuracy.
• Innovation: Stay ahead of AIOps trends (e.g., causal inference, topology-aware analytics) and evaluate new tools/techniques.
• Documentation: Create architecture blueprints, runbooks, and best practices for AIOps adoption.

Qualifications

• Education: Bachelor’s/master’s in computer science, Data Science, or related field.
• Experience: 5+ years in Observability Tools, AIOps and cloud operations, with 2+ years focused on AI/ML-driven observability.

• Technical Skills:
  • Proficiency in Selector AI or similar platforms (e.g., Moogsoft, BigPanda).
  • Expertise in AI/ML frameworks (TensorFlow, PyTorch) and observability tools (ELK Stack, OpenTelemetry).
  • Hands-on experience with cloud platforms (AWS, Azure, GCP) and containerization (Kubernetes, Docker).
  • Strong programming skills in Python, SQL.
• Soft Skills: Problem-solving, cross-functional collaboration, and excellent communication.
• Certifications (Bonus): AWS/Azure Architect, Kubernetes, or ML certifications.

Preferred Qualifications

• Experience implementing Selector AI for large-scale event correlation.
• Familiarity with big data technologies (Kafka, Spark) and CI/CD pipelines.
• Knowledge of ITIL processes and Agile methodologies.

Additional Information

All your information will be kept confidential according to EEO guidelines.