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Executive Observability Engineer Jobs in Florida

Cisco

Engineering Product Manager

Miami, FL · On-site

$159K - $165K/yr

Our work powers security, observability, AI, compliance, cost optimization, and enterprise ... Excellent executive and cross-functional communication skills, including the ability to align ...

Phsorg

Databricks and Modern Data Engineering Lead implementation and scaling of Databricks as the ... Ensure high availability, observability, and monitoring of data pipelines. Implement automated ...

ARC Group

Azure Cloud Data Engineer

Weston, FL · Remote

$108K - $130K/yr

Routine command of observability approaches for the clouds: logging, monitoring, tracing. Would you ... ARC Group is a Forbes-ranked a top 20 recruiting and executive search firm working with clients ...

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Executive Observability Engineer information

What is an executive observability engineer?

Executive Observability Engineers are specialized IT professionals who design and manage systems that monitor, analyze, and optimize the health and performance of an organization's technology infrastructure. They focus on providing high-level visibility into applications, networks, and services, enabling executives to make data-driven decisions. These engineers implement observability tools, create dashboards, and generate reports that translate complex technical metrics into actionable business insights. Their work is crucial for ensuring system reliability, quick incident response, and continuous improvement across the organization.

What are the key skills and qualifications needed to thrive as an executive observability engineer?

To thrive as an Executive Observability Engineer, you need deep expertise in performance monitoring, distributed systems, and troubleshooting, often supported by a degree in computer science or a related field. Familiarity with observability tools such as Datadog, New Relic, Prometheus, and advanced logging systems, as well as certifications like AWS Certified DevOps Engineer, is highly beneficial. Strong analytical thinking, communication, and leadership skills set top candidates apart in this role. These skills and qualities are crucial to proactively detect issues, optimize system performance, and drive strategic decision-making across complex technical environments.

What are some common challenges executive observability engineers face when implementing organization-wide monitoring solutions?

Executive Observability Engineers often encounter challenges such as integrating diverse monitoring tools across legacy and modern systems, ensuring data consistency, and balancing comprehensive visibility with system performance. Coordinating with multiple teams to align observability goals and fostering a culture of proactive monitoring can also require strong communication and leadership skills. Successfully managing these complexities leads to more resilient infrastructure and improved incident response times.

What is the difference between Executive Observability Engineer vs Site Reliability Engineer?

AspectExecutive Observability EngineerSite Reliability Engineer
CredentialsTypically requires expertise in observability tools, monitoring, and cloud platformsRequires skills in systems engineering, coding, and infrastructure management
Work EnvironmentFocuses on designing observability solutions, analyzing system health, and strategic monitoringManages system reliability, automates deployment, and maintains infrastructure
Industry UsageUsed in tech companies emphasizing system visibility and performance analysisCommon in cloud services, SaaS, and large-scale web services

The Executive Observability Engineer primarily focuses on implementing and optimizing observability tools to ensure system health, while the Site Reliability Engineer concentrates on maintaining system reliability and automating infrastructure. Both roles require technical expertise but differ in their strategic versus operational focus.

What are the most commonly searched types of Observability Engineer jobs in Florida?

The most popular types of Observability Engineer jobs in Florida are:

What are popular job titles related to Executive Observability Engineer jobs in Florida?

For Executive Observability Engineer jobs in Florida, the most frequently searched job titles are:

What job categories do people searching Executive Observability Engineer jobs in Florida look for?

The top searched job categories for Executive Observability Engineer jobs in Florida are:

What cities in Florida are hiring for Executive Observability Engineer jobs?

Cities in Florida with the most Executive Observability Engineer job openings:

Executive Observability Engineer jobs near you

Machine Learning Engineer

Roper Technologies

Sarasota, FL

Full-time

Re-posted 26 days ago

Roper Technologies rating

8.7

Company rating: 8.7 out of 10

Based on 8 frontline employees who took The Breakroom Quiz

56th of 247 rated software companies

Job description

Roper Technologies is seeking a Machine Learning Engineer to help design, build, and deploy advanced AI systems across our portfolio of market-leading software businesses. 
This role will focus on developing scalable machine learning products and services, shared AI components, and intelligent agents that drive meaningful business impact. Depending on experience level, the role may involve leading architectural initiatives, mentoring engineers, and shaping technical strategy. 
 
We are looking for hands-on engineers who are excited about building production-grade AI systems—not just prototypes—and who thrive in a high-impact, applied environment. Candidates who have demonstrated ability to think through product as well as engineering are highly desired.
 
What You’ll Do 
 
AI & ML System Development 
  • Design, build, and deploy machine learning models and AI systems in production environments 
  • Develop components such as:
    • Model inference services 
    • Data and feature pipelines
    • Complex recommendation and matching services
    • Vision based analysis systems
    • Evaluation and monitoring pipelines 
  • Optimize models for performance, reliability, and cost efficiency      
Intelligent Agents & Applied AI 
  • Contribute to the development of AI agents and multi-step workflow automation systems 
  • Build systems that integrate with enterprise tools and APIs 
  • Implement tool-use frameworks, memory mechanisms, and evaluation loops 
  • Experiment with LLMs, foundation models, and fine-tuning approaches 
  • Help translate AI research advances into practical, scalable solutions 
Engineering Excellence 
  • Write high-quality, maintainable, and well-tested code 
  • Participate in architecture design and technical reviews 
  • Contribute to CI/CD pipelines and MLOps workflows 
  • Implement observability and monitoring for AI systems in production 
  • Follow security, compliance, and responsible AI best practices 
Cross-Functional Collaboration 
  • Partner with product, data engineering, and infrastructure teams 
  • Help identify high-impact AI use cases within portfolio companies 
  • Support integration of shared AI components into business applications 
  • Communicate technical tradeoffs clearly to both technical and non-technical stakeholders 
Qualifications 
 
We welcome candidates across a range of experience levels. The scope and seniority of responsibilities will scale accordingly.  
Required 
  • 3+ years of experience in software engineering, data science, or machine learning (more for senior roles) 
  • Experience building and deploying production software systems 
  • Strong programming skills in Python (experience in additional languages is a plus) 
  • Familiarity with ML frameworks (e.g., PyTorch, TensorFlow, scikit-learn) 
  • Understanding of modern AI architectures, including LLM-based systems 
  • Experience working with cloud environments (AWS, Azure, or GCP) 
  • Strong problem-solving skills and attention to detail 
 
Preferred  
  • Experience with:
    • Fine tuning, experimentation, etc.
    • Rapid development using AI tools 
    • Agent frameworks and orchestration tools 
    • Distributed systems or microservices architecture 
    • Model monitoring and evaluation frameworks 
  • Experience building reusable libraries or shared infrastructure 
  • Exposure to SaaS products or enterprise software environments 
  • Background in optimizing models for performance and cost
Leveling & Growth 
 
We are hiring across multiple experience levels: 
  • Intermediate ML Engineer – Contributes independently to projects, builds production features, collaborates cross-functionally. 
  • Senior ML Engineer – Owns complex systems end-to-end, drives architectural decisions, mentors others. 
  • Principal / Staff ML Engineer – Defines technical direction, leads cross-portfolio initiatives, designs shared frameworks and scalable AI infrastructure. 
Level and compensation will be determined based on experience and demonstrated expertise. 
 
What We Value 
  • Strong engineering fundamentals 
  • Practical, impact-driven AI development 
  • Curiosity and willingness to experiment responsibly 
  • Ownership mindset and bias toward execution 
  • Ability to balance innovation with reliability 
Why Join Roper 
  • Work on high-impact AI systems across a diverse portfolio of leading software businesses 
  • Build reusable infrastructure that scales across industries 
  • Collaborate with experienced engineering and executive leadership 
  • Shape the next generation of intelligent enterprise software 

What Roper Technologies employees say

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