AI-First SRE/DevOps Engineer
Axiad
Salary undisclosed
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Description
Axiad is the identity security company building Axiad Mesh — the identity risk decision platform for the IVIP era. Mesh translates identity exposure into financial impact, prioritizes risk across human, machine, and agentic identities, and drives remediation through existing operational systems.
Location: US (Remote or HQ Hybrid)
Job Type: Full-time
Axiad is seeking a skilled AI-First SRE/DevOps Engineer with 5–8 years of hands-on infrastructure and platform engineering experience to help build and run Mesh, our Identity Visibility and Intelligence Platform (IVIP) — a cloud-native microservices platform on Kubernetes spanning human identity, non-human identity (NHI), post-quantum cryptography, and agentic AI identity risk. The ideal candidate has a builder mentality and a strong AI-First mindset: automation and AI are the default, not the afterthought, and infrastructure is something you create, not just maintain.
This is a startup environment. You will own real surface area end-to-end, move fast, and ship. The role requires deep operational expertise in Kubernetes, CI/CD, and infrastructure-as-code, along with practical experience running AI/LLM systems in production. If your instinct when facing a repetitive task is to script it, agent-ify it, or delete it entirely — you'll fit right in.
Role 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 and 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.
Preferred Qualifications
- 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.
120,000 - 160,000 OTE + Equity + Benefits
ABOUT US
We are a fast-moving company and are looking for candidates with growth potential, eager to learn and who can demonstrate their abilities and motivation to contribute in a fast-paced environment. Axiad offers a competitive compensation and benefits. You will work in a fun and creative environment with a talented group of individuals that have a passion for building great solutions.
About this role
Axiad is building Mesh, an identity risk platform that connects human, machine, and AI identities to financial impact. This role puts you in charge of the cloud-native infrastructure that powers it—a multi-tenant Kubernetes platform handling microservices, LLM workloads, and agentic systems. You'll own reliability and delivery end-to-end, from design through production, in a startup where a small team ships multiple times daily.
The work blends traditional SRE depth with a distinctly modern angle: you're expected to treat infrastructure as something you build and improve, not just maintain. That means designing CI/CD and GitOps pipelines that enable velocity, instrumenting everything with SLOs and distributed tracing, and—critically—embedding AI into operations itself. Automating incident response, building inference gateways, and putting AI agents into triage and remediation loops aren't nice-to-haves; they're the default. You'll need 5–8 years of hands-on platform or SRE experience, strong Kubernetes chops, and daily fluency with AI development tools like Claude Code or Cursor. Go or Python scripting, cloud-native infrastructure-as-code, and observability expertise are table stakes.
This suits someone with a builder's instinct who gets energized by startup pace and ownership. You'll collaborate directly with product and platform teams—no ticket handoffs—and mentor others in automation-first culture. If you've run LLM systems in production, worked with data pipelines, or have a security or identity background, you'll have an edge. The role offers $120–160k OTE plus equity and benefits, based in San Jose with a hybrid or remote option.
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Pay for this role
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