Senior AI-Driven DevOps Engineer — Cloud & Automation

Entrust; Dallas (TX); Hybrid; USD 140,000 - 180,000; Full time

Job summary

Entrust is seeking a Principal Application DevOps Engineer, AI & Automation to join our Cloud Services team. You will own deployment automation, observability, and AI-enabled operational capabilities, bridging R&D and Operations with a strong focus on reliability and performance.

You will lead incident triage, define health indicators, and advance automated release practices while mentoring engineers and shaping production-grade solutions across enterprise SaaS environments.

Qualifications

• Bachelor's degree in Computer Science, Software Engineering, Information Technology, or an equivalent combination of education and relevant experience.
• 10+ years of experience across software engineering, DevOps, site reliability engineering, application operations, production engineering, or related disciplines.
• Extensive experience supporting enterprise SaaS or distributed microservices applications in production environments.
• Strong software-development or scripting capability and the ability to read, troubleshoot, and improve application code and automation.
• Hands‑on experience with CI/CD, configuration automation, deployment tooling, source control, and software release practices.
• Demonstrated expertise with application performance monitoring, centralized logging, distributed tracing, alert design, and production diagnostics.
• Experience leading complex incident triage, root cause analysis, and reliability improvements across application and infrastructure boundaries.
• Experience building or integrating AI‑assisted engineering or operations solutions, including agentic AI workflows, AI agents, or tool-using automation beyond basic code generation or ad hoc analysis.
• Ability to lead through influence, mentor experienced engineers, and deliver meaningful progress in an environment with shared ownership.

Responsibilities

• Develop deep working knowledge of IFI application architecture, service dependencies, transaction flows, and common failure modes.
• Define and implement application health indicators, service-level indicators, dashboards, alerts, and diagnostic views that connect system behavior to customer and application impact.
• Advance monitoring beyond infrastructure signals by incorporating application behavior, transactions, errors, latency, dependencies, and business-process health.
• Partner with engineers and support teams to improve telemetry, logging, tracing, application diagnostics, and supportability.
• Establish standards for actionable alerting, monitoring coverage, operational runbooks, and application readiness.
• Lead application-focused triage for complex production incidents and help the team distinguish symptoms from causes.
• Use logs, metrics, traces, code-level context, database signals, and deployment history to accelerate diagnosis and recovery.
• Drive root cause analysis and corrective-action planning for recurring or high-impact issues.
• Identify reliability risks and translate findings into engineering improvements, automation, monitoring changes, and backlog items.
• Coach Cloud Services engineers in application-aware troubleshooting and production engineering practices.
• Own and improve deployment automation, CI/CD pipelines, release engineering practices, and environment promotion processes.
• Establish release standards, deployment validation, post-deployment assurance, rollback procedures, and production-readiness criteria.
• Partner with R&D to define clear operational handoffs, ownership boundaries, and support expectations for new and changed capabilities.
• Advance practices such as automated testing, progressive delivery, Blue/Green deployments, controlled cutovers, and automated recovery.
• Reduce manual steps, release risk, and dependency on individual subject matter experts.
• Identify and prioritize operational problems where AI can materially improve speed, quality, consistency, or engineering capacity.
• Design and build practical AI-assisted solutions for alert enrichment, incident summarization, triage guidance, log and telemetry analysis, deployment validation, anomaly investigation, knowledge retrieval, and corrective-action recommendations.
• Move AI opportunities from concept through prototype, validation, production implementation, adoption, and measurable outcome tracking.
• Integrate approved AI capabilities with operational data sources, monitoring platforms, delivery pipelines, knowledge repositories, and team workflows.
• Apply appropriate security, access, data-handling, validation, auditability, and human-review controls to AI-enabled operational solutions.
• Establish reusable patterns and coach engineers so AI adoption becomes a team capability rather than a collection of isolated experiments.
• Serve as a senior technical leader and change agent without requiring formal people-management responsibility.
• Influence architecture, tooling, engineering priorities, and operating practices across Cloud Services, R&D, AppOps, and related partners.
• Turn ambiguous operational needs into a clear technical approach, delivery plan, and measurable result.
• Mentor engineers through hands‑on pairing, technical reviews, troubleshooting sessions, and reusable guidance.
• Communicate technical findings and recommendations clearly to engineering, operations, product, and leadership audiences.
• Participate in scheduled daytime on-call coverage as part of a follow‑the‑sun support model and in off‑hours maintenance windows as assigned.

Skills

Observability

DevOps

CI/CD

Incident triage

AI-enabled operations

Technical leadership

Education

Bachelor's degree in Computer Science / Software Engineering

Tools

Datadog

Splunk

Jenkins

Octopus Deploy

Ansible

Terraform

GitHub

Job description

Entrust is seeking a Principal Application DevOps Engineer, AI & Automation to join our Cloud Services team. You will own deployment automation, observability, and AI-enabled operational capabilities, bridging R&D and Operations with a strong focus on reliability and performance.

You will lead incident triage, define health indicators, and advance automated release practices while mentoring engineers and shaping production-grade solutions across enterprise SaaS environments.