Description

Key Responsibilities

• Design and deploy AI/ML models supporting anomaly detection, baselining, event correlation, and predictive operational analytics.
• Build and integrate AI-enabled capabilities into enterprise Observability platforms, including Grafana, APM/RUM tools, network telemetry systems, and data observability tools.
• Develop AI Agents that can autonomously triage issues, recommend corrective actions, and initiate automated remediation workflows to reduce recovery time and improve system resilience.
• Implement self-healing automation using AI-driven decisioning, integrating with orchestration frameworks, service APIs, and infrastructure automation pipelines.
• Engineer and maintain real-time and batch data pipelines using Snowflake ML Jobs, Snowflake Cortex, streams, tasks, and UDFs.
• Implement and manage OpenTelemetry-based telemetry ingestion for logs, metrics, traces, and spans across distributed systems.
• Build asynchronous Python APIs and services for model inferencing and operational integration.
• Enhance observability intelligence with AI-powered capabilities such as root-cause acceleration, chatbot/search enablement, and automated insights.
• Contribute to SLO/SLI modeling, Golden Signals instrumentation, and Observability NFR adoption.
• Collaborate across engineering, SRE, platform, and business teams to embed proactive intelligence and Observability standards throughout the ecosystem.

Required Skills & Qualifications
Core Technical Skills

• Strong proficiency in Python and data science/ML libraries:
  • NumPy
  • Pandas
  • scikit-learn
  • TensorFlow
  • PyTorch
  • Matplotlib
  • Seaborn
• Experience with Generative AI, LLM fine-tuning, prompt engineering, RAG pipelines, and LLM evaluation frameworks.
• Expertise in developing and deploying ML models in production (batch & streaming).
• Strong understanding of statistics, time series modeling, and anomaly detection.

Observability & Telemetry

• Experience with OpenTelemetry for logs, metrics, traces, and spans.
• Familiarity with Observability concepts:
  • Golden Signals
  • SLO/SLI design
  • APM
  • RUM
  • Synthetics
  • Event correlation
  • Baselining
• Experience with Observability tools such as:
  • Grafana (Alloy agents, dashboards, ML capabilities)
  • Dynatrace
  • Monte Carlo (Data Observability)
  • Netscout
  • ThousandEyes
  • SolarWinds
  • NetBrain

Cloud, Data & Platform

• Hands-on experience with:
  • AWS (SageMaker, Bedrock)
  • Snowflake ML
  • Snowflake/Openflow
  • Snowflake AI Observability tooling
• Experience building Snowflake data pipelines (streams, tasks, UDFs); experience with Cortex features is a plus.
• Strong understanding of distributed systems and microservices telemetry requirements.

Automation & Engineering Quality

• Experience with automation pipelines, CI/CD, and Infrastructure as Code (IaC) patterns supporting Observability adoption.
• Ability to build asynchronous Python APIs or services for model inference and operational integration.

Preferred Qualifications

• Experience developing agentic AI systems that analyze telemetry, generate action recommendations, or execute automated operational responses.
• Experience building self-healing patterns, including automated rollback, service restarts, configuration corrections, and predictive maintenance.
• Experience in Snowflake ML workflows, Snowflake Cortex Agents, and data pipeline automation.
• Exposure to AI-enabled alerting, RCA automation, and operational self-healing concepts.
• Experience with large-scale operational telemetry and multi-cloud ecosystems

Key Skills

Education

Bachelor's degree