Site Reliability Engineer (SRE)

Lovelace AI, Inc.

Lovelace (NM)

On-site

USD 110,000 - 160,000

Full time

5 days ago
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Job summary

Lovelace AI, Inc. is seeking a Site Reliability Engineer to keep our AI-powered applications and infrastructure available, scalable, and fast. You’ll bridge development and operations, using automation to improve reliability and performance across our systems.

Joining this team means working with cloud platforms, containers, and IaC while collaborating with engineers to design resilient services from day one. On-call rotations and proactive incident management are part of the role.

Qualifications

  • 5+ years in site reliability engineering, DevOps, or related role.
  • Proven track record managing complex infrastructure, troubleshooting production issues, and optimizing performance.
  • Strong Linux/Unix administration and scripting (Python, Bash, Go).
  • Deep knowledge of cloud platforms (AWS, GCP, Azure) and services like EC2, S3, Lambda.
  • Hands-on experience with Docker and Kubernetes.
  • Proficiency with monitoring/observability tools (Prometheus, Grafana, Datadog, Dynatrace, ELK).
  • Networking fundamentals (DNS, HTTP, TCP/IP), load balancing, CDNs.
  • Experience with CI/CD tools (Jenkins, GitLab CI, CircleCI) and IaC.
  • Familiarity with distributed systems and microservices.

Responsibilities

  • Design, build, and maintain monitoring, alerting, and observability.
  • Lead troubleshooting of complex production issues and perform RCAs.
  • Build and maintain automation, build systems (Bazel), and IaC (Terraform, Ansible, CloudFormation).
  • Collaborate with software teams to ensure scalable, reliable services from design onward.
  • Participate in on-call rotations and incident response.
  • Analyze system performance and recommend scalability improvements.
  • Establish best practices for deployment, monitoring, and incident management.
  • Develop internal tools for operations, bug tracking, CI/CD, and cross-team communication.
  • Document post-incident reviews and solutions in a knowledge base.

Skills

SRE experience
Linux/Unix
Python/Bash/Go
Cloud platforms
Docker & Kubernetes
CI/CD
Monitoring/observability
Networking basics
Infrastructure as code

Tools

Terraform
Ansible
CloudFormation
Prometheus/Grafana

Job description

About Us:

Lovelace is the only provider of enterprise-scale context engines capable of analyzing trillions of real-time data points to create knowledge graphs that are usable by autonomous agents at the speed, scale, and accuracy required for mission-critical analysis.

Lovelace’s context engine platform, Elemental, uniquely integrates data ingestion, entity resolution, and graph building into a single pipeline that empower agentic deployments, delivering 1000X the investigative power for complex queries. With its proprietary ground-breaking YottaGraph, Lovelace provides enterprises with real-time, real-world context, enabling agents to understand the impact of global intelligence on enterprise data for unmatched insights with millisecond precision.

Founded in 2023 by Andrew Moore, former head of Google Cloud AI, dean of Carnegie Mellon’s School of Computer Science, and first AI advisor for U.S. CENTCOM, Lovelace currently works with some of the largest public and private enterprises in the world.

Job Summary:

  • Lovelace AI is looking for a Site Reliability Engineer to keep our AI-powered applications and infrastructure available, scalable, and fast. You’ll sit between software development and operations, using engineering and automation to keep our systems reliable and to improve them over time.

Key Responsibilities:

  • Design, build, and maintain monitoring, alerting, and observability so issues are caught and resolved before they reach users

  • Lead troubleshooting of complex production issues, deliver root cause analyses (RCAs), and put preventive fixes in place

  • Build and maintain automation, build systems (Bazel), and infrastructure as code (Terraform, Ansible, CloudFormation) to remove manual work and improve reliability

  • Partner with software engineering teams early in the design of new services so they are scalable, reliable, and resilient from the start

  • Participate in on-call rotations to respond to incidents, alerts, and escalations

  • Analyze system performance and recommend improvements for scalability, reliability, and efficiency

  • Establish and enforce best practices for deployment, monitoring, and incident management to reduce downtime

  • Build and maintain internal tools for operations, bug tracking, CI/CD pipelines, and cross-team communication

  • Run post-incident reviews and document problems and solutions in a shared knowledge base

  • Support vulnerability management, system patching, and security measures that protect service integrity and availability

Qualifications:

  • 5+ years in site reliability engineering, DevOps, systems administration, or a related role

  • Proven track record managing complex infrastructure, troubleshooting production issues, and optimizing performance in high-scale environments

  • Strong Linux/Unix administration skills and proficiency in scripting languages such as Python, Bash, or Go

  • Deep knowledge of cloud platforms (AWS, GCP, Azure) and their services, such as EC2, S3, and Lambda

  • Hands-on experience with containerization and orchestration using Docker and Kubernetes

  • Proficiency with monitoring and observability tools such as Prometheus, Grafana, Datadog, Dynatrace, or the ELK Stack

  • Solid grasp of networking fundamentals (DNS, HTTP, TCP/IP), load balancing, and CDNs

  • Experience with CI/CD tools (Jenkins, GitLab CI, CircleCI) and infrastructure automation

  • Familiarity with distributed systems and microservices architecture

  • Ability to define Service Level Indicators (SLIs) and align work to availability and latency objectives

Preferred Skills:

  • Excellent problem-solving, troubleshooting, and analytical skills

  • Comfortable balancing development and support responsibilities

  • Strong communication and interpersonal skills, with a track record of collaborating across teams

  • Experience working on projects that involve business segments

Benefits:

LovelaceAI offers competitive compensation packages, comprehensive benefits. We provide a supportive and inclusive work environment where your skills and expertise can make a significant impact on the safety and security of our communities.

Lovelace’s founding team includes:

Andrew Moore, who has a track record of building impactful AI systems, designing them with human rights impact assessments as a top priority, leading the AI division of one of the world’s foremost cloud companies, and actively participating in machine learning and AI research over the past two decades.

Toby Smith, well known in the Pittsburgh Tech community for his engineering leadership and design skills, and who has led many of the most ambitious and complex system infrastructure projects in Google Pittsburgh and NetApp.

Here is a note from Andrew Moore to people who are reading these Job Postings:

“Hi folks, I’m so glad you are potentially interested in Lovelace AI. This area means a lot to me because while I am an AI optimist, I also think that we technologists owe it to a rightly skeptical world to show that modern intelligent systems can actually be useful. Usefulness comes in many guises: from life sciences to education and from transportation to entertainment and many others. For many of us, security and public safety is also very high on that list. That reasoning leads to this conclusion: I’m determined to make sure that the people building Lovelace AI gain a lot from the experience, including the chance to solve fascinating problems in computer science, AI, business development, customer success and product management. I also hope that we all learn from each other in a highly enriching work environment. But my main hope is that we have a shared sense of accomplishment as we see an increasing number of national security and public safety domains made safer through sensible and robust use of advanced computer science.”

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