Job Type:
full time
|
Location:
33 Irving Pl, Manhattan, New York, United States
Post Date: 2026-06-13T00:00
Closing Date: 2026-12-31T12:00
Job Available
Job Title: Site Reliability Engineer (SRE)
Employment Type: Full-Time
Work Model: Remote (US-Based) · Optional Hybrid in New York, NY
Compensation: $145,000 – $200,000 USD per year
Reports To: Co-Founder / CEO
About LockedIn AI
LockedIn AI is a fast-growing AI career technology company trusted by over 1 million users worldwide. We build a real-time AI interview and meeting copilot that supports users during high-stakes professional moments such as interviews, coding assessments, and live meetings.
Our systems operate in real time at scale, where reliability, latency, and uptime directly impact user success. This makes infrastructure stability a core part of the product experience.
Role Overview
We are hiring a proactive, systems-minded Site Reliability Engineer to ensure that LockedIn AI’s production systems remain highly reliable, scalable, and performant.
This role sits at the intersection of infrastructure, software engineering, and operations. You will be responsible for maintaining the reliability of real-time AI systems that serve over 1 million users globally.
You will own production stability across cloud infrastructure, Kubernetes environments, AI inference systems, APIs, and real-time services.
Key Responsibilities
System Reliability & Performance
Own reliability, availability, and performance of production systems
Define and manage SLIs, SLOs, and error budgets aligned with product goals
Design fault-tolerant and self-healing system architectures
Continuously optimize system latency, throughput, and resource usage
Identify bottlenecks and improve system performance at scale
Infrastructure as Code & Cloud Systems
Design and manage cloud infrastructure across AWS, GCP, or Azure
Implement Infrastructure as Code using Terraform, Pulumi, or CloudFormation
Manage Kubernetes clusters supporting microservices and AI workloads
Ensure infrastructure is versioned, reproducible, and scalable
Optimize cloud costs while maintaining performance and reliability
Observability & Monitoring
Build observability systems using metrics, logs, and traces (Prometheus, Grafana, Datadog, ELK, etc.)
Design alerting systems that reduce noise and improve incident response
Implement distributed tracing for microservices and AI pipelines
Monitor AI-specific metrics including latency, GPU usage, and token throughput
Provide real-time visibility into system health and performance
Incident Response & Reliability Engineering
Lead incident response for production outages and system failures
Participate in on-call rotations and coordinate cross-team resolution efforts
Conduct blameless postmortems with actionable improvements
Build runbooks, playbooks, and escalation procedures
Track MTTR and reliability trends to drive continuous improvement
CI/CD & Release Engineering
Design and maintain CI/CD pipelines for safe and automated deployments
Implement canary releases, blue-green deployments, and rollback systems
Ensure AI model deployments follow the same reliability standards as application code
Add testing and validation gates to prevent production issues
Improve deployment velocity while maintaining system stability
Security & Compliance
Implement secure infrastructure practices including IAM, encryption, and secrets management
Maintain network segmentation and audit logging
Ensure privacy-first infrastructure design across all systems
Manage vulnerability scanning, patching, and system hardening
Collaborate with security teams to enforce DevSecOps practices
Required Qualifications
Experience
3+ years in Site Reliability Engineering, DevOps, or infrastructure roles
Experience owning production systems at scale
Strong background in incident response and postmortem processes
Experience in fast-paced startup or high-growth environments
Technical Skills
Strong programming ability in Python, Go, or similar
Deep experience with AWS, GCP, or Azure infrastructure
Strong Kubernetes and Docker expertise in production environments
Experience with Infrastructure as Code (Terraform, Pulumi, CloudFormation)
Hands-on experience with CI/CD systems (GitHub Actions, ArgoCD, Jenkins, etc.)
Strong knowledge of observability tools (Prometheus, Grafana, Datadog, ELK)
Understanding of distributed systems and system design principles
Soft Skills
Strong reliability-first mindset with focus on failure scenarios
Calm and structured thinking during production incidents
Clear communication across technical and non-technical teams
Strong documentation and runbook writing ability
High ownership and autonomy in system management
Preferred Qualifications
Experience with AI/ML infrastructure or GPU-based workloads
Background in real-time systems or low-latency architectures
Experience with chaos engineering practices
Knowledge of AI observability (model latency, drift, throughput metrics)
Multi-cloud or hybrid cloud experience
Contributions to open-source infrastructure or SRE tooling
Early-stage startup experience (Seed to Series A)
What We Offer
Equity
Meaningful early-stage equity and ownership in the company’s growth
Impact
Direct responsibility for systems used by over 1 million users worldwide
Team
Lean, high-ownership engineering culture with strong autonomy
Flexibility
Remote-first setup with optional collaboration in New York City
Growth
High-speed learning environment with deep technical ownership
Culture
User-first, fast execution, and engineering excellence focused on real-world impact
Why Join LockedIn AI
Work on a category-defining real-time AI copilot platform
Own reliability for systems critical to users during live interviews
Solve complex distributed systems and AI infrastructure challenges
Operate at scale with high-performance, latency-sensitive systems
Join an AI-native company building the future of career tools
How to Apply
Please submit:
Resume or CV
Short note including: Why you want to join LockedIn AI
Whether you have used the product
Suggested improvements for reliability or performance
Optional: GitHub, SRE projects, or technical writing samples
Equal Opportunity
LockedIn AI is committed to building a diverse and inclusive workplace. All hiring decisions are based on merit, skills, and business needs.
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