Lead Product Engineer – Observability; Enterprise App Monitoring - Remote
Kankakee, Kankakee County, Illinois, 60901, USA
Listed on 2026-07-03
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Software Development
AI Engineer (Applied/Software), DevOps, Cloud Engineer - Software, Software Architect
Lead Product Engineer
Allstate is seeking a forward-thinking Lead Product Engineer to drive innovation in its AI-powered Observability platform. This role sits at the intersection of AI engineering, observability, and software development, with a strong focus on automation, intelligent insights, and self-healing systems across hybrid and multi-cloud environments. You will lead the design and development of next-generation observability solutions powered by agentic AI, enabling proactive detection, diagnosis, and remediation of issues.
This role emphasizes building scalable platforms, intelligent automation, and developer-centric tooling that enhance reliability, performance, and operational efficiency. As a technical leader, you will shape product strategy, drive engineering excellence, and deliver AI-driven monitoring and automation capabilities that transform how applications and platforms are operated across the enterprise.
- Design and build agentic AI solutions for observability, including autonomous agents capable of anomaly detection, root cause analysis, and automated remediation.
- Embed AI/ML capabilities into observability platforms to enable predictive insights, anomaly detection, and intelligent alerting.
- Develop AIOps frameworks that reduce noise, automate workflows, and improve incident response times.
- Leverage LLMs and AI orchestration frameworks to create self-service diagnostics and operational assistants.
- Architect and implement end-to-end observability solutions across logs, metrics, traces, and events.
- Enhance observability platforms (Datadog, Dynatrace, New Relic, App Dynamics, OTEL) with custom integrations, automation, and AI enhancements.
- Build real-time insights and health analytics to ensure system reliability, scalability, and performance.
- Lead development of scalable, reusable platform components and APIs for observability and automation.
- Build developer-first tools and frameworks that simplify instrumentation, monitoring, and diagnostics.
- Apply modern software engineering practices including TDD, CI/CD, microservices, and cloud-native design.
- Develop full-stack solutions (backend services, dashboards, automation tooling) using Java/Spring Boot, Python, Node.js, and React.
- Drive automation-first strategies to eliminate manual operations and improve efficiency.
- Build self-healing systems that automatically detect and remediate issues.
- Lead initiatives in infrastructure-as-code, Observability-as-code and automated deployment pipelines.
- Engineer highly resilient systems by focusing on performance, scalability, and fault tolerance.
- Define and evolve enterprise observability architecture, incorporating AI and automation as core principles.
- Collaborate with architecture, platform, and security teams to align solutions with enterprise standards.
- Champion standardization, reusable patterns, and platform scalability across the organization.
- Act as a technical leader and mentor, guiding teams in AI, observability, and engineering best practices.
- Partner with cross-functional teams to deliver integrated, high-impact platform solutions.
- Communicate technical concepts and strategies effectively to both technical and executive audiences.
- Foster a culture of innovation, automation, and continuous improvement.
- 5+ years of engineering experience building software, platforms, or automation solutions, with a strong emphasis on observability and distributed systems.
- 4+ years of hands-on experience with observability platforms (Datadog, Dynatrace, OTEL).
- 3+ years of software development experience using Java (Spring Boot), Python, Node.js, or React.
- 2+ years of hands-on experience building agentic AI systems (autonomous agents, AI workflows, or AI-native applications).
- Proven ability to design and implement AI-driven automation and AIOps solutions.
- Experience integrating LLMs, orchestration frameworks, or AI pipelines into production systems.
- Strong experience with Kubernetes and cloud-native architectures.
- Hands-on experience in hybrid environments (on-prem + cloud) across Linux and Windows.
- Expertise in API development, event-driven systems, and microservices architecture.
- Famili…
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