Senior Site Reliability Engineer (Remote, India) EST
This is the employer's own posting, not a copy on a job board.
What we know
Is it still open?
Confirmed still open
Last checked 2d ago — checked against the employer's own applicant tracking system, which is the company answering directly.
We re-read the employer's own applicant tracking system and the posting was still there. That is the company answering directly.
How old is it?
Posted 24d ago
The date the source published, not the day we noticed it (2026-09-17). Last seen at its source 1h ago.
We have tracked this listing since 5 Oct 2026 (5 days). The employer's own board has carried it every time we have read it, most recently 1 hour ago.
Is it remote?
India, Remote
That is the location the employer filed this posting under. Quoted as written — we do not re-word the source's own location.
Who may apply?
India
The description states no restriction of its own. This is the source's own tag.
Pay not stated
Similar roles pay $50k–82.5k/yr
Middle 50% of 12 listings that do state pay — Engineering · all levels · India · USD/year. This employer has published no salary; this is what comparable listings we hold disclose, never converted between currencies or periods. How this is calculated.
Skills named in the ad
Recognised terms only, from a fixed vocabulary — this is what CV matching compares against.
Carried by 1 source
-
Ashby employer's own board first seen 5d ago · last seen 1h ago
The listing
Please note: This role requires working in the EST Zone (usually from 8 PM to 4 AM IST) in order to add technical coverage to US customers.
About Level AI
Level AI is on a mission to turn every customer interaction into a strategic advantage. Our AI-native platform helps enterprises transform contact centers from cost centers into engines of customer intelligence, operational efficiency, and business growth. By combining advanced AI with deep domain understanding of customer experience, Level AI empowers teams to unlock actionable insights, automate workflows, and deliver more consistent, higher-quality support across the customer journey.
Headquartered in Mountain View, California, Level AI is a Series C company backed by leading investors, including Battery Ventures and ENIAC. Our platform leverages Large Language Models and Custom Small Language Models (SLMs) to power AI Agents across the entire CX journey—customer-facing agents, agent-assist, and backend automation—along with deep conversation analytics for QA, coaching, and insights.
About the role
The Senior SRE will be positioned at the intersection of backend engineering, infrastructure operations, and FinOps. The role is explicitly broader than a traditional DevOps engineer and explicitly more hands-on than a pure architect.
What you'll be liable for:
Infrastructure cost efficiency and FinOps. Own the continued reduction of Kubernetes overprovisioning, drive right-sizing programs, and maintain the cost telemetry that backend teams use to make decisions.
GPU throughput optimization. Run a structured experimentation program on on-premise GPU clusters, partnering with AI service owners. Led by the Engineering leadership, with this role providing the experimental bandwidth.
Backend enablement, not ownership absorption. Build the tooling, dashboards, and processes that let backend teams from other groups own their own cost and reliability budgets. The deliverable is leverage, not headcount-shaped work.
Reliability instrumentation. As the infra team owns most of the instrumentation across new and offline flows, this role takes a central seat in making sure that surface area is captured properly for both cost-at-scale and reliability.
Selective security workstreams. Take on a defined slice of the active security work so that senior DevOps engineers are not the single point of execution for security-adjacent platform changes.
We'd love to explore more about you if you have:
This role explicitly requires 4-5 years of hands-on systems experience. We are not looking for someone who will lean entirely on AI tooling to discover what to do; we are looking for someone who already knows what to ask and can use AI tooling as a force multiplier on top of that judgement.
Backend engineering depth: production experience in Python, Go/Rust, comfortable owning services end to end, able to read and reason about backend code across teams.
Kubernetes at scale: scheduler behaviour, resource requests/limits, HPA/VPA, node pool design, cost-aware autoscaling (Cast AI, Karpenter, or equivalent).
Cloud and on-premise infrastructure: GCP fluency, IaC (Terraform), CI/CD, and comfort operating in hybrid setups, including on-prem GPU clusters.
GPU workload understanding: familiarity with throughput profiling, batching, KV-cache behavior, inference server tuning, and GPU utilisation metrics.
Observability and reliability: metrics, traces, logs, SLOs, and the discipline to instrument systems properly rather than reactively.
FinOps mindset: demonstrated history of converting infrastructure choices into measurable cost outcomes.
Security baseline: able to take on platform-security workstreams without requiring constant handoff to the DevOps team.
Can work in the EST time zone (A must)