Senior DevOps Engineer, AI Platform

Location: San Jose, California; hybrid workplace

Company

hirify.global develops SaaS products for accounting workflows, including Transform, AI Matching, and AutoBuilder.

What you will do

• Own the AWS Bedrock and Bedrock AgentCore runtime across US, EU, and AU regions, including model access, throughput, quotas, throttling, retries, and regional availability.
• Operate sandboxed execution environments for AI-generated code with lifecycle limits, network controls, least-privilege IAM, and tenant isolation.
• Build and review Terraform for a multi-account, multi-region AWS estate running on ECS/Fargate and Lambda.
• Extend Grafana observability with token usage, latency, throttling, retries, tool-call failures, sandbox outcomes, generation success, and end-to-end traces.
• Manage AI cost attribution, capacity planning, SLOs, CI/CD gates, feature-flagged releases, and rollback workflows.
• Join the DevOps on-call rotation and create runbooks for model throttling, sandbox exhaustion, queue failures, and silent degradation.

Requirements

• 5+ years of experience in DevOps, SRE, platform, or infrastructure engineering with production on-call ownership.
• Deep hands-on AWS experience with ECS/Fargate, Lambda, SQS, S3, IAM, VPC, networking, and ALB/NLB.
• Production-scale Terraform experience, including modules, state management, multi-region, and multi-account infrastructure.
• Experience operating an LLM-backed or ML-serving workload in production, with practical knowledge of tokens, latency, throttling, and cost.
• Experience with CI/CD, Docker, GitHub Actions, Grafana, Prometheus or OpenTelemetry, distributed tracing, and user-journey SLOs.
• Working fluency in Python or TypeScript/Node.js and the ability to read and debug the other language.

Nice to have

• Multi-region infrastructure under US/EU/AU data-residency constraints.
• AI cost and performance optimization, sandboxed untrusted-code execution, FinOps, or per-tenant attribution.
• Atmos or comparable Terraform orchestration, NX/Turborepo/Bazel, and Harness feature flags.
• Exposure to MongoDB, PostgreSQL, Snowflake, EMR/Spark, or regulated SaaS domains such as fintech, accounting, or healthcare.
• SOC 2 or ISO 27001 audit evidence experience.

Culture & Benefits

• Embedded collaboration with the Transform and Close AI engineering pods.
• Production systems are operated with an emphasis on reliability, observability, security, compliance, and cost control.
• AI infrastructure is deployed across US, EU, and AU regions and defined entirely in Terraform.
• Model and prompt changes are versioned, evaluated in CI, feature-flagged, and reversible.

Hiring process

• 30-minute recruiter screen followed by approximately four hours of interviews.
• Hiring manager discussion, technical deep dive with Terraform and service diagnosis, and AI infrastructure design exercise.
• Team panel with engineering, security or compliance, and engineering-values discussions.