DevOps Platform Engineer

We are the Platform-as-a-Service Engineering team at EarnIn. We don’t just manage infrastructure; we build the foundational "Paved Road" that enables our product teams to ship with velocity and safety. Our stack is built on AWS, EKS, and Argo CD, but our future is Agentic. We are shifting from manual configuration to AI-augmented orchestration, in which the platform anticipates developers' needs and self-heals through intelligent automation. We're seeking a Platform Engineer (I3) who is an AI-native builder, someone who doesn't just use AI tools but designs and deploys AI agents to eliminate toil, accelerate developer workflows, and multiply what a lean team can deliver. You will own solutions across Kubernetes (AWS EKS), GitOps (Argo CD), CI/CD (GitHub Actions), and our developer portal (Cortex), while relentlessly automating repetitive operational work through agentic AI.

As an I3 engineer, you are a professional contributor who effectively represents the team's perspective and communicates across functions. You will collaborate with DevX, SRE, and Product Engineering peers to turn fragmented workflows into AI-powered golden paths, building agents that handle incident triage, environment provisioning, config generation, and developer self-service, so engineers can focus on high-value work rather than tickets, aligned with our Platform Engineer growth matrix.

• AI-Agent Development: Design, build, and iterate on AI agents that automate platform operations, from service and infra bootstrap, intelligent incident diagnosis, automated runbook execution, to self-healing infrastructure and PR-review bots. Own the agent lifecycle: prompt engineering, tool/function-call orchestration, evaluation, and production monitoring.
• Workflow Automation with AI: Identify and eliminate repetitive human-in-the-loop workflows across CI/CD, environment management, access provisioning, and change management.
• Kubernetes Infrastructure: Support our Kubernetes platform on AWS EKS, with a focus on environment hygiene and security; execute cluster-level tasks and updates with minimal support, and leverage AI for anomaly detection, capacity recommendations, and automated remediation.
• Developer Experience: Utilize our developer control plane (Cortex) to maintain paved paths and self-service actions, helping teams move from idea to production with minimal friction.
• Observability & Excellence: Strengthen operational excellence by monitoring SLOs/error budgets and utilizing Datadog for metrics, traces, and logs to improve system reliability.
• Platform Development: Develop platform services using industry best practices that enable operational excellence for Data, CI/CD, and Security.
• Service Standardization: Maintain service scaffolds and templates that encode testing and telemetry standards, ensure alignment with platform baselines, and use AI to auto-generate and validate configurations against them.

WHAT WE'RE LOOKING FOR 

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
• 3+ years in platform, infrastructure, or backend engineering with deep knowledge of Kubernetes (EKS) and cloud-native architectures on AWS.
• Demonstrated experience building AI agents or agentic workflows, not just using Copilot or ChatGPT, but designing multi-step AI systems that autonomously perform operational tasks (e.g., LLM-powered runbook agents, intelligent CI/CD bots, self-service assistants with tool-use/function-calling).
• Track record of automating away repetitive workflows with AI. You should be able to point to specific examples in which you replaced manual processes with AI-driven automation, enabling a team to do more with fewer resources.
• Experience in GitOps (Argo CD) and CI (GitHub Actions) for multi-service systems.
• Strong coding skills in Go and/or Python, treating infrastructure as software.
• Excellent communication skills; able to clearly convey technical issues and advocate for both the team's and the customer's needs.
• Experience with LLM orchestration frameworks (e.g., LangChain, LlamaIndex, CrewAI, or custom agent architectures) and prompt engineering for production systems.
• Mission-Driven: A strong advocate for the customer who takes initiative to fix issues and constantly asks, "Can an AI agent do this instead of a human?"
• Experience with service mesh (e.g., Linkerd) and traffic management patterns is a plus. 
• Hands-on contributions to developer productivity insights and observability for cost-aware engineering decisions are a plus. 

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