# Senior Platform Engineer

**Company**: EarnIn
**Location**: Mountain View, US
**Work arrangement**: hybrid
**Experience**: senior
**Job type**: full-time
**Salary**: $228,000-$279,000
**Category**: Engineering
**Industry**: Technology

**Apply**: https://job-boards.greenhouse.io/earnin/jobs/8335328?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply
**Canonical**: https://yubhub.co/jobs/job_c9bf4e65-fff

## Description

## About the Role

We are seeking a Senior Platform Engineer to join our team at EarnIn. As a Senior Platform Engineer, you will design, build, and operate the agentic systems and core infrastructure that power our platform.

## Responsibilities

- AI-Agent Design and Build: Design, build, and operate AI agents in production, following established governance patterns for model selection, evaluation, and safety.

- Technical Execution: Implement agentic patterns for cloud infrastructure in your area of ownership, applying and helping refine team best practices for production AI agents.

- Platform Operations: Operate and improve high-availability distributed systems on AWS, identifying and resolving performance, scalability, and stability issues within your domain.

- Developer Platform: Contribute to the evolution of our developer control plane (Cortex) as an AI-augmented self-service platform, building features that let engineers scaffold services, debug deployments, and resolve issues through natural language.

- Reliability and Documentation: Document agentic architecture, best practices, and operational procedures for the systems you build.

## Requirements

- Bachelor's or Master's degree in Computer Science, Engineering, or related field.

- 4+ years in cloud infrastructure, working on large-scale, high-availability, customer-facing distributed systems.

- Experience mentoring junior engineers and leading well-scoped platform initiatives within your team.

- Hands-on experience building and operating AI-driven systems in production, including agentic workflows that perform operational tasks.

- Strong working knowledge of AWS (EKS, Lambda, Bedrock, etc.) and experience with containerized and serverless architectures.

- Solid expertise in Kubernetes at scale and ability to implement complex, resilient solutions with guidance from senior/staff engineers.

- Strong knowledge of infrastructure-as-code tools (Terraform, Ansible) and experience applying both traditional IaC and agentic automation.

- Strong command of Datadog and observability practices, using metrics to drive decisions.

- Experience building AI-driven alerting or root-cause analysis systems is a plus.

- Strong adherence to security, privacy, and compliance best practices, with awareness of governance considerations for production AI systems (model safety, prompt injection prevention, data isolation).

- Experience with LLM orchestration frameworks (LangChain, LlamaIndex, CrewAI, or custom agentic architectures) and production prompt engineering.

- Strong coding ability in Python and/or Go, with experience treating infrastructure and agentic systems as software.

- Ability to collaborate effectively across engineering, product, and security teams on cross-functional work.

- Experience with service mesh (Linkerd, Istio) and traffic management at scale is a plus.

- Proficiency with GitOps (Argo CD, Flux CD) and CI/CD orchestration (GitHub Actions, Argo Workflows) is a plus.

- Experience with MLOps or LLMOps concepts (model versioning, evaluation frameworks, production monitoring for AI systems) is a plus.

- Familiarity with security frameworks relevant to AI systems (guardrails, audit logging, data governance for LLMs) is a plus.

## Benefits

The base salary range for this full-time position is $228,000-$279,000, plus equity and benefits.

## Skills

### Required
- AWS
- Kubernetes
- Python
- Go
- Terraform
- Ansible
- Datadog
- AI-driven systems
- agentic workflows
- LLM orchestration frameworks
- production prompt engineering
- infrastructure-as-code tools
- containerized and serverless architectures
- security, privacy, and compliance best practices

### Nice to have
- service mesh
- traffic management at scale
- GitOps
- CI/CD orchestration
- MLOps
- LLMOps
- security frameworks relevant to AI systems

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Source: [Apply at job-boards.greenhouse.io](https://job-boards.greenhouse.io/earnin/jobs/8335328?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply)