1

Director Observability Jobs in Madison, WI (NOW HIRING)

Expertise in web performance strategies, optimization techniques, and observability/monitoring for ... Direct experience with cloud platforms, specifically GCP (Google Cloud Platform), including managed ...

... and observability. For more information, visit www.enterprisedb.com As EDB Principal Customer ... Direct experience working with globally distributed and remote customer and internal teams

Director Observability information

What does a director of observability do?

A Director of Observability leads the strategy and implementation of monitoring, logging, and tracing systems to ensure the health and performance of technical infrastructure. They work with engineering and operations teams to develop best practices, select appropriate tools, and set standards for observability across the organization. Their goal is to provide visibility into system behavior, quickly identify and resolve incidents, and support continuous improvement in system reliability and performance.

How does a director of observability typically collaborate with engineering and operations teams to drive organizational goals?

A Director of Observability works closely with engineering and operations teams to ensure that systems are monitored effectively and issues are identified and resolved quickly. This collaboration often involves developing unified monitoring strategies, aligning observability tools and processes, and facilitating incident response post-mortems. The Director also leads cross-functional meetings to establish best practices, set key performance indicators (KPIs), and ensure observability is integrated into the software development lifecycle. By acting as a bridge between technical teams, they help foster a culture of transparency, reliability, and continuous improvement.

What are the key skills and qualifications needed to thrive as a director of observability, and why are they important?

To thrive as a Director of Observability, you need deep expertise in monitoring, logging, and distributed systems, typically backed by a degree in computer science or a related field and extensive experience in IT or DevOps leadership roles. Proficiency with observability tools such as Prometheus, Grafana, Datadog, Splunk, and APM solutions, along with knowledge of cloud platforms and relevant certifications, is essential. Strong leadership, strategic thinking, and communication skills help drive cross-functional initiatives and foster a culture of reliability. These skills and qualities are crucial for ensuring system health, rapid incident response, and alignment between technical teams and organizational objectives.

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

AspectDirector ObservabilitySite Reliability Engineer
Primary FocusOversees observability strategies, tools, and teams to ensure system visibility and performanceBuilds and maintains reliable systems, automates deployment, and manages incident response
CredentialsTypically requires advanced knowledge of monitoring, cloud platforms, and leadership experienceOften has software engineering background, with skills in scripting, automation, and systems engineering
Work EnvironmentLeads teams in tech companies, focusing on monitoring and analytics toolsWorks closely with development and operations teams to ensure system reliability

While both roles focus on system performance and reliability, the Director Observability primarily manages observability strategies and teams, whereas the Site Reliability Engineer is hands-on, building and maintaining reliable systems. The roles complement each other in ensuring optimal system performance and uptime.

What are popular job titles related to Director Observability jobs in Madison, WI?

For Director Observability jobs in Madison, WI, the most frequently searched job titles are:

What job categories do people searching Director Observability jobs in Madison, WI look for?

The top searched job categories for Director Observability jobs in Madison, WI are:

Infographic showing various Director Observability job openings in Madison, WI as of August 2026, with employment types broken down into 96% Full Time, and 4% Contract. Highlights an 82% In-person, and 18% Remote job distribution.

Director of Applied AI & ML Engineering

Paradigm

Middleton, WI • On-site

Other

This job post has expired today. Applications are no longer accepted.


Job description

Job Description
Job Description

Paradigm is a software company transforming the way that the residential construction & building product industries operate across the globe. We are looking for a Director, Applied AI & ML Engineering to be part of revolutionizing these industries.

The Director, Applied AI & ML Engineering will lead the strategy, architecture, and deployment of intelligent systems that transform how homes are designed, estimated, and built. This role will drive the integration of AI and machine learning across the residential construction lifecycle—from digital plan understanding and takeoffs to automated estimating, material optimization, and design personalization.

The ideal leader blends technical depth with strategic clarity—able to guide teams across computer vision, large language models, and agentic automation while ensuring reliable, scalable delivery within the construction domain.

What You Will Do:

  • Define and lead the Applied AI & ML strategy for residential construction, identifying and prioritizing use cases that enhance speed, accuracy, and efficiency.

  • Build and maintain a roadmap of agentic AI systems that automate key construction workflows—such as plan interpretation, quantity takeoffs, cost estimation, and material specification optimization, while enabling seamless integration with suppliers, ERP platforms, and technology providers.

  • Partner with Product, Engineering, and Operations leaders to embed AI capabilities into core platforms and customer-facing applications.

  • Lead the design of AI-powered and multi-agent systems that connect workflows across design, estimating, procurement, and field execution.

  • Architect retrieval-augmented generation (RAG) and computer vision pipelines that interpret plan sets, generate takeoffs, and surface contextual insights.

  • Combine LLMs, CV, and rule-based logic to deliver explainable and auditable systems tailored to construction professionals.

  • Ensure architectural scalability, performance, and observability in all deployed systems.

  • Oversee the end-to-end ML lifecycle—from experimentation and model development to deployment, monitoring, and iteration.

  • Implement best practices in MLOps, data management, and continuous delivery pipelines.

  • Deliver measurable improvements in model quality, reasoning accuracy, and cost efficiency through advanced evaluation methods, such as Evals, zero- and few-shot benchmarking, Chain-of-Thought, and LLM-as-a-judge techniques to guide continuous model refinement.

  • Build, mentor, and lead a cross-functional team of applied AI and ML engineers, partnering closely with product, design, and software engineering teams to deliver production-grade AI-powered systems.

  • Foster a culture of collaboration, experimentation, and responsible AI development.

  • Manage vendor relationships and technology partnerships across cloud and AI platforms.

  • Collaborate with design, estimating, and operations teams to identify automation opportunities and ensure successful adoption.

  • Translate complex AI concepts into clear direction for business and product stakeholders.

  • Represent the organization’s AI vision in external partnerships, technical forums, and industry collaborations.

What You Need to Succeed:

  • 12+ years of experience in applied AI, ML, and/or Software engineering, with at least 5 years in a leadership role.

  • Bachelor’s or advanced degree in Computer Science, Machine Learning, or a related field preferred.

  • Proven success designing and deploying AI-driven systems in production environments.

  • Expertise in LLMs, computer vision, multimodal models, and retrieval-augmented generation (RAG) architectures.

  • Strong foundation in modern software engineering—including APIs, microservices, CI/CD, and containerization.

  • Hands-on familiarity with ML platforms such as MLflow, Kubeflow, or SageMaker for model training and deployment.

  • Demonstrated ability to collaborate across engineering, product, and operations in a complex technical environment.

  • Excellent written and verbal communication skills for both technical and executive audiences.

  • Experience in residential construction technology, including estimating, takeoffs, or design automation is preferred.

  • Background in BIM/CAD integration, digital twin platforms, or 3D modeling workflows is preferred.

  • Familiarity with agent orchestration frameworks (Temporal, n8n, LangGraph) and enterprise API integration is preferred.

  • Understanding of AI governance, auditability, and human-in-the-loop validation frameworks is preferred.

  • Experience with Azure, AWS, or GCP cloud platforms for scalable AI deployment is preferred.

Ready to Join? Apply now! MyParadigm.com/careers/
#Paradigm