EarnIn - Software Engineer II
Requirements
• 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.
Responsibilities
• 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.
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