Note: The job is a remote job and is open to candidates in USA. Axiad is seeking an AI-First SRE/DevOps Engineer to build and operate Mesh, its cloud-native identity visibility and intelligence platform. The role owns platform reliability, observability, delivery, infrastructure automation, and production AI/LLM infrastructure, while helping engineers adopt AI-first operational practices.

Responsibilities

• Own reliability, observability, and delivery for a multi-tenant, cloud-native Kubernetes platform — from design through production, yours to run and yours to improve
• Build (not just operate) CI/CD pipelines, infrastructure-as-code, and GitOps-driven progressive delivery that let a small team ship many times a day, safely
• Embrace and advocate AI-First operations: automate incident response, runbooks, and remediation, and put AI agents in the loop to triage, diagnose, and propose fixes where it makes sense. Treat toil as a bug
• Build the infrastructure that AI-native features run on: inference gateways, LLM cost/latency observability, prompt/version pipelines, eval harnesses, and guardrails for agentic workloads
• Instrument everything — SLOs, error budgets, and distributed tracing across services and data pipelines
• Harden the platform: secrets management, supply-chain security, and least-privilege everywhere
• Troubleshoot and resolve production issues, leveraging AI-powered debugging and observability tooling
• Collaborate directly with product and platform engineers to translate requirements into resilient infrastructure — no throwing tickets over a wall; if you see a problem, it's yours to solve
• Mentor engineers in adopting AI-first operational practices and automation-by-default culture

Skills

• 5–8 years of professional experience in SRE, DevOps, or platform engineering roles
• Builder mentality: you'd rather create a tool, platform, or automation than run a manual process twice. You ship things and stand behind them
• Ownership: you take problems from ambiguity to resolution without waiting for a ticket, a spec, or permission. When something you own breaks, you're the first to know and the first to act
• Strong Kubernetes operational experience — running it in production, not just deploying to it
• Demonstrable adoption of an AI-First mindset and tools (Claude Code, Cursor, or Windsurf)
• Daily use of at least one AI development tool is a must
• Fluency with infrastructure-as-code, GitOps, and modern CI/CD; comfortable scripting and building tooling (Go or Python preferred)
• Cloud-native depth on at least one major cloud provider
• Solid observability expertise and SLO-driven operations experience
• Experience with containerization (Docker) and service mesh concepts
• Strong problem-solving skills and a collaborative mindset; excellent communication within Agile teams
• A bias for shipping — startup pace energizes you rather than stresses you
• Experience building or operating LLM infrastructure: inference gateways, eval/observability tooling, agentic orchestration
• Data-pipeline and streaming/CDC experience
• Security or identity background; familiarity with post-quantum cryptography or supply-chain security
• Prior experience at an early-stage startup

Benefits

• Equity
• US (Remote or HQ Hybrid)

Company Overview

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