Base Salary
$186k - $282k/yr
Responsibilities
- Own the AWS Bedrock and Bedrock AgentCore footprint across US, EU, and AU, including model access, throughput, cross-region inference, quotas, throttles, and availability.
- Operate sandboxed execution environments for AI-generated code with session limits, network controls, and least-privilege IAM.
- Write and review Terraform for a multi-account, multi-region AWS estate.
- Build AI workload observability covering token consumption, latency, throttles, retries, tool-call failures, sandbox outcomes, generation success, and agent traces.
- Define journey-based SLOs and operate AI-specific reliability and on-call runbooks.
- Engineer AI cost attribution and controls across inference, serving, sandbox compute, and telemetry.
- Build GitHub Actions pipelines for Node/TypeScript and Python services, with versioned, evaluated, feature-flagged, and reversible model and prompt changes.
- Plan capacity for peak accounting workloads and enforce tenant isolation, audit logging, encryption, patching, and asset inventory.
- Inventory and instrument the AI runtime, eliminate infrastructure drift, establish cost baselines, and document reusable runtime patterns.
Requirements
- 5+ years of experience in DevOps, SRE, platform, or infrastructure engineering, including production systems supported through on-call.
- Deep hands-on AWS experience with ECS/Fargate, Lambda, SQS, S3, IAM, VPC/networking, and ALB/NLB.
- Production-scale Terraform experience with modules, state management, multi-region, and multi-account infrastructure.
- CI/CD and container ownership experience, including GitHub Actions, Docker, image supply chains, and scaling policies.
- Production experience operating an LLM-backed or ML-serving workload, with concrete knowledge of tokens, latency, throttling, and cost.
- Experience with observability tools such as Grafana, Prometheus, or OpenTelemetry, distributed tracing, and user-experience-focused SLOs.
- Working fluency in Python or TypeScript/Node.js and ability to read and contribute to services in the other.
- Preferred experience includes multi-region data-residency infrastructure, AI cost and performance optimization, sandboxed untrusted-code execution, Terraform orchestration, monorepo build systems, progressive delivery, FinOps, data infrastructure, audit evidence, and regulated SaaS.
- Model training, fine-tuning, research publications, accounting experience, and a PhD or formal ML credential are not required.
Benefits
- Medical, dental, vision, family-forming benefits, life and disability insurance, unlimited vacation, and participation in an employee stock program.
- The position has a stated base pay range of $186,000-$282,000 per year.
- The interview process includes a 30-minute recruiter screen followed by approximately four hours of hiring manager, technical, design, and team-panel conversations.
Tech Stack
Categories
About FloQast
FloQast is the AI Accounting Transformation Platform built by accountants, for accountants. Accounting is entering its AI era. FloQast is building the platform that defines it. We understand the different nuances in how accounting is managed from company to company -- business growth leads to increased complexity, yet teams are faced to respond without additional resources. It's why our Agents are designed to automate specific accounting workflows without compromising security or auditability. Our ISO 42001 certification can attest the accountant retains the final judgement call and has full visibility into all agent interactions. More than 3,500 global teams, including Lululemon, Chipotle, and Shopify, rely on FloQast to reduce manual work, strengthen compliance, and move from preparation to strategic review with confidence. We are not replacing accountants. We are equipping them with AI built for the way accounting actually works. Through our free FloQast Certified Accountant program, we are also investing in the next generation of AI enabled accounting professionals.