AI-First SRE/DevOps Engineer
Build and run a cloud-native Kubernetes platform for an AI-first identity security product, automating operations with AI agents and modern DevOps tooling.
- Compensation
- $120K–$160K / yr
- Location
- San Jose, California, United States
- Work setup
- Not specified
- Seniority
- Not specified
- Employment
- Full time
- Experience
- 5+ years
- Category
- Devops
- Posted
Skills
Nice to have
- 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.
Full 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.