Senior Observability Engineer

Jones Lang LaSalle Incorporated; Ciudad de México; On-site; MXN 1,200,000 - 2,000,000; Full time

Job summary

Jones Lang LaSalle (JLL) is seeking a Senior Observability Engineer to design and implement enterprise observability with Datadog, across our global technology estate. You will lead strategic initiatives, develop AI-first reliability, and collaborate across infrastructure, cloud, and application teams to improve visibility and automation.

This role offers growth, exposure to AIOps, and opportunities to influence architectural decisions at scale.

Qualifications

• Bachelor's degree or equivalent in a technical field.
• 5–8+ years in observability, monitoring, SRE, or related roles with leadership.
• Hands-on Datadog implementation in large-scale environments.
• Experience with automation and IaC practices.

Responsibilities

• Lead observability workshops and incident response across APAC, AMER, and EMEA.
• Architect enterprise observability with reliability considerations.
• Drive monitoring standards and prioritization.
• Champion observability strategy across tech initiatives.

Skills

Datadog expert

Automation & orchestration

Python scripting

REST APIs & CI/CD

Multi-cloud (Azure/AWS)

Observability concepts

Education

Bachelor's degree in Computer Science / IT / Engineering

Tools

Datadog

Rundeck

Ansible

Python

PowerShell

Bash

Git/GitHub

CI/CD tools

Job description

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 peopleand 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, establishingbest 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 allocatedand priorities are set
• Champion observability strategy as part of broader technology initiatives while leading transformation projects that modernize how wemonitorand operate services

Advanced Technical Implementation

• Build, configure, and optimize Datadog capabilities across infrastructure, applications, networks, cloud platforms, logs, and digital experience monitoring with AI-firstmethodology
• 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
• Identifyopportunities to reduce operational toil,eliminatealert fatigue,optimizetelemetry costs, and improve signal-to-noise ratio whilemaintainingcomprehensive 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 whilemaintainingenterprise 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 demonstratedtechnical 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 levelobjectives, and error budgets with demonstratedability to architect solutions at enterprise scale
• Advancedexpertisewith automation and orchestration technologies such asRundeckand Ansible, with proven ability to build AI-enhanced operational solutions
• Strongproficiencyin 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 demonstratedsuccess integrating observability into enterprise workflows
• Expert-level knowledge of major cloud platforms, particularly Azure and AWS; GCP experience beneficial, with demonstratedmulti-cloud operational capabilities
• Deep familiarity with Infrastructure as Code (IaC) and configuration management practices, with hands‑on experience applying observability-as-code methodologies

Preferred qualifications

• Provenexpertiseacross multiple observability domains including infrastructure monitoring, APM, log analytics, network performance monitoring, cloud monitoring, and digital experience monitoring with ability to architect solutions spanning multiple domains
• Extensive hands‑on experience with AIOps capabilities such as anomaly detection, event correlation, intelligent alerting, and automated incident analysis with track recordof leading AI strategy and implementation
• Demonstrated experience with generative AI and AI-assisted engineering, particularly applications that accelerate observability, automation development, troubleshooting effectiveness, and operational efficiency
• Proventrack recordleading high‑visibility, cross‑functional initiatives and delivering organizational value through process innovation and technology modernization
• Relevant certifications in Datadog, cloud technologies (AWS Certified Solutions Architect, Azure Administrator, GCP Professional Cloud Architect), automation, SRE, or related disciplines
• Exceptional communication and influencing skills withdemonstratedability to work effectively in globally distributed teams, drive transformational change, and shape strategic decisions across APAC, AMER, and EMEA time zones

Location

On-site –Distrito Federal,MEX

At JLL, we harness the power of artificial intelligence (AI) to efficiently accelerate meaningful connections between candidates and opportunities. Using AI capabilities, we analyze your application for relevant skills, experiences, and qualifications to generate valuable insights about how your unique profile aligns with the specific requirements of the role you’re pursuing.

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Jones Lang LaSalle(“JLL”) is an Equal Opportunity Employer and is committed to working with and providing reasonable accommodations to individuals with disabilities. If you need a reasonable accommodation because of a disability for any part of the employment process – including the online application and/or overall selection process – you may email us at [e-mail]. This email is only to request an accommodation. Please direct any other general recruiting inquiries to our Contact Us page.

Jones Lang LaSalle(“JLL”) está comprometida a trabajar con personas con discapacidades y proporcionarles accesibilidad. Si necesita un ajuste razonable para cualquier parte del proceso de empleo – incluyendo la candidatura en línea y/o el proceso general de selección – puede enviarnos un correo electrónico a [e-mail]. Este correo electrónico es solo para solicitar un ajuste razonable. Por favor, dirija cualquier otra consulta general de reclutamiento a nuestra página Contáctanos.