Open-Source Observability and AIOps platforms Expert

2 days ago

Navi Mumbai, Maharashtra, India Orange Business Services Full time ₹ 12,00,000 - ₹ 36,00,000 per year

Key Responsibilities

  • Define and enforce best practices, governance frameworks, and standards for observability and AIOps implementations.
  • Design and Deploy observability solutions using open-source toolsets (Prometheus, Grafana, Loki, Tempo, ELK/OpenSearch, Open Telemetry etc)
  • Build scalable and resilient observability platforms across multi-cluster and multi-cloud environments; establish MELT strategies; optimize storage efficiency and query performance
  • Applying AIOps methodologies and machine learning techniques to observability data for automated event correlation, anomaly detection, root cause analysis, and predictive insights
  • Design and deploy RAG-based architectures to enable contextual incident triaging, intelligent knowledge retrieval, and accelerated root-cause analysis.
  • Integrate Large Language Models (LLMs) with observability platforms to support incident summarization, and AI-driven recommendations.
  • Leverage advanced analytics to detect performance bottlenecks in observability/AIOps platforms and implement proactive optimizations.
  • Drive data governance initiatives in collaboration with cross-functional teams to ensure data quality, privacy, and security.
  • Stay abreast of emerging trends in open-source observability, AIOps, and LLM technologies to drive business-aligned strategies

Mentor and upskill junior team members by developing technical content, documentation, and training materials.

Skills & Qualification

  • 810 years of extensive experience in observability, monitoring, and AIOps solutions across enterprise environments
  • Proven hands-on expertise in implementing open-source observability stacks (OpenTelemetry, Prometheus, Grafana, Loki, ELK/OpenSearch, etc.).
  • Demonstrated experience in AIOps solution design and implementation, including noise reduction, event correlation, anomaly detection, and predictive analytics.
  • Strong proficiency in containerization and orchestration technologies (Kubernetes, Docker) and cloud-native architectures.
  • Experience working with major cloud platforms (AWS, Azure, GCP) for large-scale, distributed observability deployments.
  • Skilled in scripting and automation using Python, Ansible, Bash, and Terraform.
  • In-depth knowledge of APIs, data pipelines, and integration frameworks for telemetry ingestion and processing.
  • Solid understanding of Retrieval-Augmented Generation (RAG) architectures and practical experience integrating Large Language Models (LLMs) into enterprise observability workflows..
  • Excellent analytical, problem-solving, and communication skills, with the ability to collaborate effectively across cross functional teams

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