AI-First SRE/DevOps Engineer

Axiad is an identity security company building Axiad Mesh, an identity risk decision platform for the IVIP era. The AI-First SRE/DevOps Engineer will build and operate a cloud-native Kubernetes platform, owning reliability, observability, CI/CD, infrastructure-as-code, AI/LLM infrastructure, security, and production troubleshooting.

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

Requirements:

• 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