below marketmost similar roles pay hereabove market
This role pays less than
99%
of similar roles. Most pay
$174,914–$230,500
— the blue band above.
At the midpoint, this role pays about
$144k
versus about
$203k
for comparable roles.
Based on 240 similar postings.
Employer
About Early Warning Services
Early Warning Services is a fintech company that operates the Zelle person-to-person payments network, the Paze digital checkout wallet, and Certos fraud prevention and identity risk solutions for financial institutions.
Early Warning Services currently has
84 open roles
on FindRole.
Listed pay typically runs
$145,000–$176,000
across 34 roles with salary data.
The Staff Software Engineer - AIOps is a senior hands-on technical contributor responsible for designing, building, and operating the AIOps agent platform. This role focuses on the software systems, control loop, tool interfaces, telemetry, and evaluation capabilities required to run agentic capabilities safely in production. You will build the core agent runtime, including event ingestion, context assembly, planning, and tool invocation. Key responsibilities include designing auditable tool interfaces for Kubernetes, network services, and ITSM platforms while implementing safety controls like blast-radius limits and emergency shutdowns. You will utilize Python, TypeScript, React, and Next.js, while working with Kafka, RabbitMQ, OpenTelemetry, Prometheus, and Grafana. The work involves solving complex problems in automated system reliability, observability, and operational risk within a highly regulated financial technology environment.
What does a Software Engineer earn in Arizona?
Median $162050 from 32 postings across 10 companies.
Design, build, and operate the core agent runtime for event ingestion, planning, and tool invocation.
Develop scoped and auditable tool interfaces for CI/CD platforms, Kubernetes, and ITSM systems.
Implement safety controls including human approval requirements, permission boundaries, and emergency shutdown protocols.
Build event-routing capabilities to prioritize alerts, tickets, and operational requests for the agent runtime.
Establish telemetry standards for logs, metrics, and traces across relevant technology platforms.
Design and operate model routing, session management, retries, and cost/latency controls for production services.
Implement comprehensive auditability for all agent decisions and actions to meet risk and compliance requirements.
Develop evaluation capabilities for agent decision quality using historical incident replay and shadow-mode testing.
What we're looking for
Must independently possess the eligibility to work in the United States at the date of hire.
Bachelor's degree in computer science, engineering, or a related technical field.
Typically eight or more years of related experience in software engineering, platform engineering, distributed systems, DevOps, AIOps, or a related technical discipline.
Strong production development experience with Python, including services, APIs, automation, orchestration systems, or agent runtimes.
Hands-on experience developing production agentic systems, tool-using AI applications, or autonomous or semi-autonomous software control loops.
Experience designing tool-use or function-calling interfaces for AI agents using MCP or comparable integration patterns.
Experience with event-driven architectures and messaging technologies such as Kafka, Pub/Sub, or RabbitMQ.
Experience with production observability practices including structured logging, metrics, and distributed tracing using OpenTelemetry, Prometheus, or Grafana.
Experience developing front-end solutions using modern frameworks such as React, Next.js, or Angular, along with backend development using TypeScript or Python.
Experience with agent orchestration frameworks such as LangGraph (preferred).
Go development experience (preferred).
Experience with CI/CD platforms, infrastructure automation, Kubernetes operations, ITSM platforms, or technology operations (preferred).
Experience leading a complex AIOps or agent-platform capability from design through production implementation (preferred).
Experience with anomaly detection, time-series analysis, or related machine-learning applications (preferred).
Experience with chaos engineering, simulation, historical incident replay, or game-day testing for distributed or automated systems (preferred).
Experience mapping automated-system controls to regulatory or control frameworks such as PCI DSS, SOX ITGC, NYDFS Part 500, or FFIEC guidance (preferred).
Experience in FinTech, banking, payments, or another highly regulated industry (preferred).
Current AWS, Kubernetes, AI engineering, security, or other relevant technical certification (preferred).