Senior Back-end Engineer; Infrastructure & Reliability

🎨 Opus Clip is the world's No.1 AI video agent, built for authenticity on social media.

We envision a world where everyone can authentically share their story through video, with no expertise needed. Within just 18 months of our launch, over 10 million creators and businesses have used Opus Clip to enhance their social presence.

We have raised $50 million in total funding and are fortunate to have some of the most supportive investors, including Soft Bank Vision Fund, DCM Ventures, Millennium New Horizons, Fellows Fund, AI Grant, Jason Lemkin (Saa Str), Samsung Next, GTMfund, Alumni Ventures, and many more.

Check out our latest coverage by Business Insider featuring our product and funding milestones, and our recognition as one of The Information's 50 Most Promising Startups in 2024.

Headquartered In Palo Alto, We Are a Team Of 100 Passionate And Experienced AI Enthusiasts And Video Experts, Driven By Our Core Values

• Be a Champion Team
• Prioritize Ruthlessly
• Ship fast, Quality Follows
• Obsess over customers

Be a part of this exciting journey with us!

We are looking for a hands‑on Founding SRE to own the reliability and scalability of the Opus Clip platform. You will stabilize our processing clusters, design isolated environments for our largest Enterprise partners, and serve as the technical bridge between infrastructure and our 15M+ users.

You will engineer the infrastructure strategy that underpins our trust and reliability in the market. You will help setup oncall rotation and own the full incident lifecycle from minimizing Time-to-Detect to tracking post mortem actions ensuring that our high‑velocity growth never compromises our performance.

• Architect Dedicated Environments:
  Lead the design and implementation of high‑throughput, isolated processing clusters for Enterprise clients. You will build the "paved road" to ensure strict High Availability (HA) without noisy neighbor interference.
• Scale Production:
  Drive general improvements in our Temporal clusters and production Kubernetes environments. You will operationalize scaling strategies that support both self‑serve consumers and high‑touch Enterprise contracts.
• Technical Execution:
  Be hands‑on with the stack to optimize resource allocation, reduce latency, and enforce isolation strategies for critical accounts.

• Beat the Customer to the Alert:
  Overhaul our Datadog observability suite to aggressively reduce Time-to-Detect (TTD). You ensure we identify latency spikes and stalled projects before users do.
• Threshold Tuning: tune alert thresholds to eliminate noise and focus on "symptom‑based" alerts that reflect the actual user experience.
• External SLO Ownership:
  Define and report on Service Level Objectives (SLOs), acting as the internal guarantor that we are meeting the targets we sold.

• First Responder & Mitigation:
  Serve as the first line of defense during outages. You will own immediate mitigation, including cluster debugging and manual scaling intervention if Horizontal Pod Autoscalers (HPA) fail or lag.
• Drive Recovery Metrics:
  You are accountable for shortening Time-to-Mitigation (TTM) and Time-to-Recover (TTR). Your priority is to stop the bleeding first, then fix the wound.
• Root Cause Analysis:
  Lead the post‑mortem process to determine Time-to-Root Cause and implement systemic fixes. You will translate these technical findings into clear updates for Customer Experience (CX) and Leadership.
• Accountability:
  Work collaboratively with Engineering Owners to track improvements against the reliability roadmap. You are responsible for flagging risks early and resetting expectations on platform performance when necessary.
• Cross-Functional Bridge:
  Serve as the primary technical voice to the Customer Experience (CX), Sales, and Leadership teams. You will translate technical constraints and roadmaps into clear, honest updates for stakeholders.

• Production K8s & Temporal:
  Expert‑level ability to debug Kubernetes internals (HPA logic, node scaling) and operate stateful workflow engines (Temporal) at…