Description

Design and deploy AI/ML models for anomaly detection, predictive analytics, and autonomous remediation within enterprise observability platforms.

This role is on-site.

Responsibilities

• Build and integrate AI-enabled capabilities into Grafana, APM/RUM tools, and network telemetry systems.
• Develop AI agents to autonomously triage issues, recommend actions, and initiate automated remediation workflows.
• Engineer real-time and batch data pipelines using Snowflake ML Jobs, Cortex, streams, tasks, and UDFs.
• Implement OpenTelemetry-based telemetry ingestion for logs, metrics, traces, and spans across distributed systems.
• Collaborate with SRE and platform teams to embed proactive intelligence and observability standards.

Required Skills

• 5+ years of experience with Python, NumPy, Pandas, scikit-learn, TensorFlow, and PyTorch.
• Strong understanding of statistics, time series modeling, and anomaly detection.
• Experience with Generative AI, LLM fine-tuning, prompt engineering, RAG pipelines, and evaluation frameworks.
• Proficiency in deploying ML models in production (batch & streaming).
• Hands-on experience with AWS (SageMaker, Bedrock) and Snowflake ML pipelines.
• Experience with observability tools such as Grafana, Dynatrace, SolarWinds, or Monte Carlo.
• Strong understanding of distributed systems, microservices telemetry, and CI/CD patterns.

Preferred Skills

• Experience building agentic AI systems for automated operational responses.
• Familiarity with self-healing patterns, including automated rollback and predictive maintenance.

Key Skills

Education

Bachelor's degree