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Why this role exists FloQast's AI products have outgrown the infrastructure patterns the rest of the platform runs on. Transform, AI Matching, and AutoBuilder are customer-facing products carrying real accounting workloads, and they behave nothing like a CRUD service. They call foundation models in multiple regions, execute generated code in sandboxes, spend money per token rather than per request, and fail in ways a 500-rate dashboard never catches. Today, DevOps engineers carry this work alongside the wider fleet. We are making it someone's whole job. You will embed with the Transform and Close AI pods and own the AI runtime the way our other embedded DevOps engineers own their business unit's platform. This is a DevOps role with an AI infrastructure specialization, not a research or modeling role. You will not train models or tune prompts for accuracy. You will make the systems that serve them fast, observable, multi-region, cost-bounded, and auditable . The products you'll support Transform. FloQast's data transformation and analytics product: a monorepo of containerized services on AWS, including an agentic LLM thread runtime, a natural-language-to-SQL service, and queue-driven workflow workers. You'll own the foundation-model runtime across our US, EU, and AU regions, sandbox isolation for AI-executed code, autoscaling for the worker fleet, and cost attribution for model spend. AI Matching. The automated reconciliation matching stack in our Close product line: LLM-backed match scoring, a matching copilot service family, and a regression harness that guards matching quality. You'll own throughput and unit economics at close-cycle peak, the sandbox for AI-generated code, and keeping the eval harness running in CI so a model or prompt change cannot ship blind. AutoBuilder. The Transform capability that generates transformation workflows and scripts for users instead of making them hand-build each one. You'll own generation-queue health and backpressure, triage that distinguishes a model failure from an infrastructure failure, scale-to-demand behavior for spiky load, and the latency budget for a user waiting on a generated artifact.
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
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When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.
