Site Reliability Engineer

LockedIn AI is the #1 real-time AI interview and meeting copilot, trusted by over 1 million users worldwide. We are building the most advanced AI-powered career preparation platform that helps users succeed in interviews, coding assessments, and professional communication.

Our platform delivers real-time AI assistance during live conversations — where reliability, speed, and uptime are mission-critical.

Role Overview

We are looking for a proactive, systems-minded Site Reliability Engineer (SRE) to ensure that LockedIn AI’s production systems are highly reliable, scalable, and performant.

This is a high-impact engineering role where system stability directly defines user experience. When users are in live interviews, latency and uptime are the product.

You will own the reliability of real-time AI infrastructure serving over 1 million users globally.

Key Responsibilities

1. System Reliability & Performance

• Own uptime, reliability, and performance across production systems
• Define and manage SLIs, SLOs, and error budgets
• Build fault-tolerant and self-healing architectures
• Optimize latency, throughput, and system efficiency

2. Infrastructure as Code & Cloud Systems

• Design and manage cloud infrastructure using Terraform, Pulumi, or CloudFormation
• Operate AWS, GCP, or Azure-based production environments
• Manage Kubernetes clusters and microservices infrastructure
• Optimize cloud costs while maintaining performance and reliability

3. Observability & Monitoring

• Build monitoring systems using Prometheus, Grafana, Datadog, or similar tools
• Design alerting systems with low noise and high accuracy
• Implement distributed tracing and centralized logging
• Monitor AI-specific metrics (latency, GPU usage, inference throughput)

4. Incident Response & Reliability Engineering

• Lead incident response for outages and production issues
• Participate in on-call rotations
• Conduct postmortems and root cause analysis
• Build runbooks and improve system resilience over time

5. CI/CD & Release Engineering

• Build and maintain CI/CD pipelines for fast and safe deployments
• Implement canary, blue-green, and rollback strategies
• Ensure safe deployment of application and AI model updates
• Improve deployment velocity without compromising stability

6. Security & Infrastructure Best Practices

• Implement secure infrastructure design (IAM, encryption, secrets management)
• Maintain compliance with privacy and security standards
• Manage vulnerability scanning and system hardening
• Ensure secure handling of user data across systems

Required Qualifications

Experience

• 3+ years in SRE, DevOps, or infrastructure engineering
• Experience managing production systems at scale
• Strong background in incident response and system reliability
• Experience working in fast-paced startup environments

Education

• Bachelor’s degree in Computer Science, Engineering, or related field
• Equivalent hands-on experience strongly considered

Technical Skills

• Strong programming skills (Python, Go, or similar)
• Experience with AWS, GCP, or Azure
• Kubernetes and Docker expertise
• Infrastructure as Code (Terraform, Pulumi, CloudFormation)
• CI/CD systems (GitHub Actions, GitLab CI, Jenkins, ArgoCD)
• Observability tools (Prometheus, Grafana, Datadog, ELK, etc.)

Soft Skills

• Strong reliability-first engineering mindset
• Calm and effective under production incidents
• Excellent communication and documentation skills
• Strong ownership and proactive problem-solving

Preferred Qualifications

• Experience with real-time AI or ML infrastructure
• Knowledge of GPU-based or inference-heavy systems
• Experience with streaming, WebSockets, or low-latency systems
• Familiarity with chaos engineering practices
• Multi-cloud or hybrid-cloud experience
• Experience in SaaS, edtech, or AI startups
• Open-source infrastructure contributions

What We Offer

Equity

Meaningful early-stage ownership in a fast-growing AI company

Impact

Your work directly supports over 1 million active users

Team

Join a lean, high-performance engineering team

Flexibility

Remote-first with optional hybrid work in New York

Growth

Fast-paced startup environment with high ownership

Culture

User-focused, feedback-driven, and execution-oriented

Why Join LockedIn AI?

• Category-defining AI interview copilot platform
• Massive and fast-growing AI career tech market
• Reliability directly impacts real-time user experience
• Work on cutting-edge AI infrastructure at scale
• High ownership and real production responsibility

How to Apply

Please submit:

• Resume / CV
• Short note covering:
  • Why you want to join LockedIn AI
  • Whether you’ve used the product
  • Ideas for improving reliability or performance
• Optional: GitHub, projects, or technical writing

Equal Opportunity Statement

LockedIn AI is committed to building a diverse and inclusive team. We welcome applicants from all backgrounds. Hiring decisions are based on merit, skills, and business needs.