Senior AI Platform Engineer

About EarnIn

As one of the first pioneers of earned wage access, EarnIn builds products that deliver real-time financial flexibility for people living paycheck to paycheck. Community members access their earnings as they earn them, with options to spend, save, and grow their money without mandatory fees, interest rates, or credit checks. The company has experienced leadership, world-class funding partners including A16Z, Matrix Partners, DST, and Ribbit Capital, and a healthy core business with strong runway.

EarnIn is becoming an AI-native company, embedding AI agents into how the organization builds, analyzes, and operates across every function. Teams use AI Agents to move from ideas to execution faster, allowing people to focus on judgment, creativity, and hard problems while agents handle repetitive tasks. This experimentation is paired with strict review and security guardrails required by the regulated financial environment, with a focus on privacy and the people who rely on the products.

About the Role

The Platform-as-a-Service Engineering team at EarnIn builds the foundational "Paved Road" that enables product teams to ship with velocity and safety. The stack is built on AWS, EKS, and ArgoCD, with a future focused on Agentic systems. The team is shifting from manual configuration to AI-augmented orchestration, where the platform anticipates developer needs and self-heals through intelligent automation.

As a Senior Platform Engineer, you will design, build, and operate the agentic systems and core infrastructure that power the platform. You will work across Kubernetes (AWS EKS), GitOps (Argo CD), CI/CD (GitHub Actions), and the developer portal (Cortex), building AI agents and automation that reduce operational toil and increase platform leverage for engineering teams across EarnIn.

As a Senior engineer, you will independently design and implement solutions for well-scoped but complex problems, re-architect components, adopt new technologies, and improve existing processes with minimal guidance. You will build agents that handle real slices of incident triage, environment provisioning, config generation, and developer self-service, and partner with Staff engineers and your manager to align your work with the team's broader technical direction.

Responsibilities

• AI-Agent Design and Build: Design, build, and operate AI agents in production, following established governance patterns for model selection, evaluation, and safety. Contribute to infrastructure-as-code practices for agentic systems, ensuring prompts, tools, and evaluation criteria are versioned, reviewed, and tested like any other critical component.

• Technical Execution: Implement agentic patterns for cloud infrastructure in your area of ownership, applying and helping refine team best practices for production AI agents. Support and mentor less experienced engineers on agentic patterns, LLM integration, and prompt engineering as opportunities arise.

• Platform Operations: Operate and improve high-availability distributed systems on AWS, identifying and resolving performance, scalability, and stability issues within your domain. Use AI-driven observability and anomaly detection to catch problems early. Evolve infrastructure-as-code and automation standards for the services you own, incorporating agentic pattern recognition and automated remediation where it adds value.

• Developer Platform: Contribute to the evolution of the 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. Help encode platform standards and security policies into AI-powered golden paths.

• Reliability and Documentation: Document agentic architecture, best practices, and operational procedures for the systems you build. Participate in on-call rotations, and use post-mortems as a feedback loop to improve system reliability and the team's agentic automation.

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. You should be able to speak to specific agent designs or automation you've built.
• Experience reducing operational toil through agentic AI (e.g., LLM-powered incident diagnosis, intelligent CI/CD with test selection, self-service assistants) on at least one meaningful workflow.
• 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.

Compensation and Location

• Base salary range: $228,000–$279,000, plus equity and benefits.
• Position type: Full-time, hybrid in Mountain View (Headquarters). Requires in-office work 2 days a week.
• Work authorization: Applicants must be currently authorized to work in the United States. EarnIn can support H-1B and O-1 employer transfers but cannot provide new visa sponsorship or consider candidates working pursuant to OPT or CPT for this position.

About Our Interview Process

At EarnIn, you are encouraged to use AI tools throughout much of your interview process. If you use AI during the live interview, simply mention how it helped and why you are using it. The evaluation focuses on your judgment, reasoning, and ability to own and defend your work, not whether AI was involved. Some rounds, particularly those focused on your career history and past experiences, will not allow the use of AI; you will be notified of these in advance. When in doubt, ask your recruiter or interviewer directly.

Diversity and Equal Opportunity

EarnIn believes that the best way to build a financial system that works for everyday people is by hiring a team that represents the diverse community. The team is diverse in background, experience, and perspective. EarnIn celebrates its diversity and strives to create a culture of belonging. EarnIn does not unlawfully discriminate based on race, color, religion, sex (including pregnancy, childbirth, breastfeeding, or related medical conditions), gender identity, gender expression, national origin, ancestry, citizenship, age, physical or mental disability, legally protected medical condition, family care status, military or veteran status, marital status, registered domestic partner status, sexual orientation, genetic information, or any other basis protected by local, state, or federal laws. EarnIn is an E-Verify participant.

EarnIn does not accept unsolicited resumes from individual recruiters or third-party recruiting agencies in response to job postings. No fee will be paid to third parties who submit unsolicited candidates directly to hiring managers or HR team.