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.