Senior Observability Engineer

JLL empowers you to shape a brighter way.
Our people at JLL are shaping the future of real estate for a better world by combining world class services, advisory and technology for our clients. We are committed to hiring the best, most talented people and empowering them to thrive, grow meaningful careers and to find a place where they belong. Whether you’ve got deep experience in commercial real estate, skilled trades or technology, or you’re looking to apply your relevant experience to a new industry, join our team as we help shape a brighter way forward.
What this job involves:
As a Senior Observability Engineer, you'll lead the design and implementation of enterprise observability solutions across JLL's global technology estate, with primary focus on Datadog. You'll architect AI-powered reliability solutions that deliver measurable business outcomes while serving as a recognized subject matter expert with organization-wide influence. Working across infrastructure, network, cloud, and application environments, you'll drive visibility improvements, establish automation standards, and enable teams to derive maximum value from observability data.
At JLL, we are collectively shaping a brighter way, and your expertise will be instrumental in making operations smarter, faster, and more reliable. You'll provide technical guidance and mentorship on enterprise observability practices while maintaining strategic alignment between technical execution and business objectives. This role offers the opportunity to work with cutting-edge AIOps and AI capabilities while solving complex technical challenges and leading transformational initiatives that define how we operate at scale.
What your day-to-day will look like:
Strategic Leadership & Enterprise Architecture:
Lead observability workshops and major incident response coordination across APAC, AMER, and EMEA regions, establishing best practices and coaching engineers on operational excellence
Architect enterprise-scale observability solutions with comprehensive reliability considerations, reviewing and influencing design decisions across multiple teams
Drive organizational improvements in monitoring standards and practices, influencing how resources are allocated and priorities are set
Champion observability strategy as part of broader technology initiatives while leading transformation projects that modernize how we monitor and operate services
Advanced Technical Implementation:
Build, configure, and optimize Datadog capabilities across infrastructure, applications, networks, cloud platforms, logs, and digital experience monitoring with AI-first methodology
Develop sophisticated dashboards, monitors, alerts, integrations, SLIs, SLOs, and service health views that enable data-driven operational decisions
Configure and troubleshoot Datadog agents, integrations, APIs, collectors, and telemetry pipelines, applying advanced analytical approaches to resolve complex operational challenges
Build scalable automation using Rundeck, Ansible, Python, PowerShell, APIs, and Git-based workflows that standardize observability onboarding, configuration management, self-healing remediation, and platform operations
Innovation & Business Impact:
Establish observability-as-code practices and create reusable patterns, frameworks, and solutions for adoption across the enterprise
Configure and optimize AIOps capabilities including event correlation, anomaly detection, intelligent alerting, noise reduction, and incident enrichment while integrating AI into operational workflows
Leverage generative AI and AI-assisted engineering to enhance observability effectiveness, accelerate troubleshooting, improve root-cause analysis, and streamline automation development
Identify opportunities to reduce operational toil, eliminate alert fatigue, optimize telemetry costs, and improve signal-to-noise ratio while maintaining comprehensive visibility
Cross-Functional Influence:
Integrate Datadog with enterprise platforms such as ServiceNow, Rundeck, cloud services, and CI/CD pipelines to create cohesive operational ecosystems
Investigate and resolve sophisticated application and infrastructure performance issues using metrics, logs, traces, events, and network telemetry while collaborating with globally distributed teams
Shape product and platform strategies through observability leadership, communicating complex technical concepts and building consensus on operational approaches
Drive adoption of transformational changes across multiple teams, ensuring quality and consistency of operational deliverables while maintaining enterprise standards
Required qualifications:
Bachelor's degree in Computer Science, Information Technology, Engineering, or related technical discipline, or equivalent combination of education and professional experience
5–8+ years of progressive experience in observability, monitoring, Site Reliability Engineering (SRE), infrastructure engineering, application performance monitoring, or related enterprise technology roles with demonstrated technical leadership
Deep hands-on experience implementing, configuring, and supporting Datadog in large-scale enterprise environments with proven organization-wide impact
Expert understanding of modern observability concepts including metrics, logs, traces, telemetry, distributed tracing, alerting, service level objectives, and error budgets with demonstrated ability to architect solutions at enterprise scale
Advanced expertise with automation and orchestration technologies such as Rundeck and Ansible, with proven ability to build AI-enhanced operational solutions
Strong proficiency in scripting and automation using Python, PowerShell, Bash, or similar languages with experience creating enterprise automation frameworks
Extensive experience working with REST APIs, webhooks, Git/GitHub, and CI/CD technologies with demonstrated success integrating observability into enterprise workflows
Expert-level knowledge of major