Senior AI Ops Engineer - Application
Core
Build and operate high-throughput ingestion pipelines, anomaly-detection models, and LLM-based log parsing/summarization components for application operations in a regulated financial environment.
Role type
Senior AI Ops Engineer (Application)
Builds
Production model-driven root-cause analysis, incident-triage solutions, and automated remediation workflows for application-layer failures.
Domain
Financial services / Application Operations / AIOps
Deliverable
production ML models
Required skills
Python, TensorFlow, PyTorch, scikit-learn, workflow orchestration, runbook-as-code, model lifecycle management, LLM prompt design, event correlation, alert grouping, high-volume telemetry analysis, model governance, drift detection
Preferred skills
Production model-driven root-cause analysis, incident-triage solutions, tested guardrails and kill-switch capabilities, AI evaluation frameworks, enterprise AIOps platforms (Moogsoft, BigPanda, Dynatrace), model risk validation
Technologies
Dynatrace, LLM, PyTorch, Python, TensorFlow, API
Responsibilities
Build and operate high-throughput ingestion pipelines for application logs, traces, and business-transaction events; Train, validate, and tune anomaly-detection and forecasting models; Develop LLM-based log parsing and root-cause-hypothesis components with hallucination safeguards; Design event-correlation logic to reduce alert volume; Write and version remediation automation with rollback and approval gates; Instrument and monitor models in production and join on-call rotation for live actions.
Seniority
Senior, hands-on IC
