Lead Product Engineer AIOps Observability; Remote
Chicago, Cook County, Illinois, 60290, USA
Listed on 2026-10-20
-
Software Development
AI Engineer (Applied/Software), DevOps, Cloud Engineer - Software, Software Architect
Job Description
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.
Key Responsibilities- 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
. - Familiarity with CI/CD pipelines, infrastructure-as-code, and Dev Ops practices
. - Strong problem-solving skills with a focus on automation and innovation
. - Excellent communication skills to articulate complex technical solutions.
- Passion for emerging technologies, particularly AI in observability and operations
.
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