Senior AIOps Engineer

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🕒 May 4

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PORCH 💚

WebsiteLinkedInAll Job Openings

1 - 10 employees

Founded 2022

🤝 B2B

👥 B2C

Insurance • B2B • B2C

PORCH 💚 is a next-generation insurance company that provides comprehensive software and services to various home service industries. It streamlines interactions for home professionals, utility customers, realtors, and homeowners by offering tools for inspections, moving, mortgage processes, and home maintenance. Through its partnerships, Porch enhances the home buying experience by simplifying service requests, onboarding new customers for warranty and insurance companies, and assisting with home improvement projects.

📋 Description

• Own production reliability for AI/ML services • Define and maintain SLOs/SLIs for critical AI systems • Build and improve AI observability • Collaborate with data scientists and ML engineers to streamline deployment workflows for models • Provision, deploy, configure, and maintain new AI infrastructure components • Optimize LLM costs • Participate in an on-call rotation for AI/ML systems • Collaborate across disciplines • Develop and maintain production-grade services and tooling in Python

🎯 Requirements

• Bachelor’s degree in Computer Science, Engineering, or related field (Master’s preferred) • 4+ years of professional software engineering experience, including at least 3 years in commercial software engineering or production operations (SRE/DevOps/Platform/ML platform), operating services on Kubernetes and/or major cloud platforms • Strong GCP experience preferred, including hands-on work with: GKE (Kubernetes Engine), BigQuery (data warehousing, SQL, schema management), Pub/Sub (event messaging), Vertex AI (batch prediction, model deployment), Cloud SQL, GCS, IAM • Experience operating production systems at scale (preferably distributed, microservices- or Kubernetes-based architectures) • Hands-on experience with CI/CD tools and deployment automation (GitLab CI/CD, GitHub Actions, or similar) • Understanding of basic machine learning concepts and model lifecycles (training, evaluation, deployment, monitoring), and familiarity with common ML tooling. • Familiarity with LLM ecosystem tooling — AI gateways, vector databases, RAG pipelines, embedding models, or LLM evaluation frameworks — is a strong plus.

🏖️ Benefits

• medical insurance • accident insurance • retiral benefits • 12 company-paid holidays • 2 flexible holidays • privilege/earned leave • casual/sick leave • paid maternity and paternity Leaves • weekly wellness events