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Spector.ai

Industrial AI platform for plant reliability

DevOps Engineer

DevOps EngineeringConfirmed live in the last 24 hours
Full-timeBengaluru, Karnataka, IndiaNo salary listedIn-person

About the Job

Requirements

  • At least 5 years of professional experience as a DevOps Engineer, Site Reliability Engineer, or similar role.
  • Demonstrated experience working within a seed-stage startup or building an environment from the ground up.
  • Understanding of resource constraints, rapid pivoting, and the hands-on generalist nature of a seed-stage environment.
  • Strong experience with Docker and Kubernetes, including Amazon Elastic Kubernetes Service, Google Kubernetes Engine, or Azure Kubernetes Service.
  • Expert proficiency with Terraform or similar Infrastructure as Code tools.
  • Experience setting up and maintaining continuous integration and continuous delivery pipelines, such as GitLab CI, GitHub Actions, or Jenkins.
  • Experience with database administration, including PostgreSQL, MongoDB, or Redis.

Responsibilities

  • Design, deploy, and maintain highly available and scalable infrastructure using Infrastructure as Code principles, such as Terraform and CloudFormation, across different cloud environments.
  • Build, maintain, and optimize organization-wide continuous integration and continuous delivery pipelines.
  • Implement and manage monitoring, logging, and alerting systems, such as Prometheus, Grafana, and the ELK stack, to ensure the health and performance of services.
  • Establish and enforce security best practices across the infrastructure and application stack, including secrets management, network segmentation, and vulnerability patching.
  • Identify and implement strategies to optimize cloud expenditure without compromising performance or reliability.
  • Work closely with the engineering team to streamline development workflows, troubleshoot production issues, and provide infrastructure support.

Desired Qualifications

  • Experience in MLOps and building production serving infrastructure for machine learning models.
  • Security certifications or extensive experience with cloud security frameworks.
  • Experience in on-premises deployment and observability.
  • Experience building and deploying machine learning models for real-time time-series data such as sensor or Internet of Things data.

About the Company

Spector.ai

Industrial AI platform for plant reliability

Spector provides an Agentic Twin platform for plant reliability and performance in industrial settings. AI agents learn how assets behave and continuously monitor equipment, delivering diagnostics and recommendations that operators can trust, with deployment available in weeks in the cloud or on-premises. It covers Asset Reliability, Process Reliability, Performance Optimization, and Plant Analysis and Troubleshooting, using a unified foundation to monitor asset health and optimize operations across sectors like oil and gas, chemicals, power, and manufacturing. The goal is to put plant reliability and performance on autopilot, helping operators maintain high uptime as experienced staff retire.

Company size
11-50
Company stage
Early VC
Total funding
$6.7M
Headquarters
San Jose, CA
Founded
2023

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