Senior Platform Engineer (AI Focused)

EarnIn; Bengaluru; Hybride; INR 4 000 000 - 7 000 000; Plein temps

Avantages offerts par ce poste

Healthcare

Internet reimbursement

Learning stipend

Travel to Mountain View

Résumé du poste

EarnIn is seeking a Senior Platform Engineer (AI Focused) to design, build, and operate AI-assisted capabilities within our platform. You will work across Kubernetes, CI/CD, GitOps, observability, FinOps, and infrastructure-as-code to embed AI into our systems powering software delivery.

You will join the Platform Engineering team, splitting time between standard platform engineering and AI engineering to ship production-grade AI workflows inside existing systems.

Qualifications

• Bachelor's or master's degree in Computer Science, Engineering, or related field, or equivalent practical experience.
• 4+ years in platform, infrastructure, or backend engineering with hands-on production experience in cloud environments (AWS preferred).
• Strong coding skills in Python and/or Go and production services.
• Deep experience with Kubernetes (EKS), GitOps (Argo CD), CI/CD (GitHub Actions), and Infrastructure as Code tools (Terraform/Helm/Kustomize).
• Solid observability skills (Datadog APM/metrics/tracing/logs) and a track record of reliability improvements.
• Hands-on experience building or integrating MCP servers and AI workflows in production environments.
• Experience with FinOps, cost attribution, and AI spend controls.
• Familiarity with LLM gateway/router patterns for cost control and observability.

Responsabilités

• Design and build MCP servers exposing platform capabilities to AI agents and developer tools.
• Create structured, agentic workflows for platform operations including incident triage and deployment validation.
• Operationalize LLM-based features with prompting, RAG, and evaluation harnesses; implement gateways for cost control and observability.
• Advance GitOps-based CD and Kubernetes infrastructure on AWS EKS; manage IaC with Terraform, Helm, and Kustomize.
• Enhance observability and reliability with SLOs, error budgets, metrics, traces, and automation to reduce MTTR/MTTD.
• Extend the developer control plane with self-service actions and scorecards.
• Instrument platform cost signals and build FinOps automation to surface waste and guide decisions.
• Define success metrics and run time-bound experiments to measure impact on efficiency, reliability, and cost.
• Document usage guidance and best practices to ensure consistent AI workflow adoption.

Connaissances

Python

Go

Observability

AI workflows

Communication

Cost optimization

MCP servers

CI/CD

SRE practices

Formation

Bachelor's or Master's degree in Computer Science or related field

Outils

Kubernetes (EKS)

GitOps (Argo CD)

CI/CD (GitHub Actions)

Terraform

Helm

Kustomize

Datadog

Description du poste

As one of the first pioneers of earned wage access, our passion at EarnIn is building products that deliver real-time financial flexibility for those with the unique needs of living paycheck to paycheck. Our 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.

We’re fortunate to have an incredibly experienced leadership team, combined with world-class funding partners like A16Z, Matrix Partners, DST, Ribbit Capital, and a very healthy core business with a tremendous runway. We’re growing fast and are excited to continue bringing world-class talent onboard to help shape the next chapter of our growth journey.

POSITION SUMMARY

As a Senior Platform Engineer (AI Focussed), you will design, build, and operate AI‑assisted capabilities within platform‑owned infrastructure and developer tooling. You will work across Kubernetes, CI/CD, GitOps, observability, FinOps, and infrastructure‑as‑code to embed AI directly into the systems that power software delivery — from MCP servers, LLM Gateways, and agentic workflows to automated diagnostics and cost optimisation.

You will join the Platform Engineering organization. The team’s mission is to provide reliable, scalable tooling that helps engineers build, test, deploy, and operate software efficiently. In this role, you will split your time between standard platform engineering and AI engineering, with a focus on shipping production‑grade AI‑assisted workflows inside existing systems.This is a hands‑on engineering role. Success is measured by real adoption and measurable improvements in developer efficiency, platform reliability, and operational cost.

This position will be a hybrid role based in our Bengaluru office, with 2 days on‑site as part of our expanding site.

• healthcare
• internet/cell phone reimbursement
• a learning and development stipend
• potential opportunities to travel to our Mountain View HQ

Our salary ranges are determined by role, level, and location.

We are unable to provide visa sponsorship or immigration support for this position.

WHAT YOU'LL DO

• Design and build MCP servers that expose platform capabilities as safe, well‑scoped tools for AI agents and developer‑facing assistants. Contribute to enterprise MCP patterns, LLM tooling, agentic guardrails, knowledge repositories, and framework rollout.
• Design structured, agentic workflows for platform operations — incident triage, deployment validation, config remediation, capacity planning — and drive AI‑assisted code review and developer tooling (e.g., CodeRabbit, Claude/Cursor) with tool‑use, validation steps, and human‑in‑the‑loop gates.
• Operationalize LLM‑based features inside platform tooling: structured prompting, RAG, output validation, and evaluation harnesses. Implement LLM gateway and router patterns to control costs, route models, and enable observability of AI workloads.
• Design and evolve GitOps‑based continuous delivery, Kubernetes infrastructure on AWS EKS, and infrastructure‑as‑code with Terraform, Helm, and Kustomize.
• Strengthen observability, reliability, and operational excellence: SLOs, error budgets, metrics/traces/logs, and automation that improves MTTD/MTTR.
• Extend the developer control plane with paved paths, scorecards, and self‑service actions.
• Instrument platform cost signals — compute, observability, and AI/LLM spend — and build FinOps automation that surfaces waste and supports cost‑aware engineering decisions.
• Define success metrics upfront and run time‑bound experiments to evaluate impact on developer efficiency, reliability, and cost.
• Document usage guidance, patterns, and best practices to support consistent adoption of proven AI workflows.

WHAT WE'RE LOOKING FOR

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field, or equivalent practical experience.
• 4+ years in platform, infrastructure, or backend engineering with hands‑on experience operating production systems in a cloud environment (AWS preferred).
• Strong coding skills in Python and/or Go, with experience building and operating production services.
• Deep experience with Kubernetes (EKS preferred), GitOps (Argo CD), CI/CD (GitHub Actions), and Terraform/Helm/Kustomize for infrastructure automation, service mesh..
• Solid observability skills (Datadog APM/metrics/tracing/logs) with a track record of improving reliability and driving SLO/error‑budget culture.
• Hands‑on experience building or integrating MCP servers — designing tool surfaces, managing scope and auth, and connecting AI agents to real infrastructure.
• Practical experience with structured or agentic AI workflows (e.g., planning/execution separation, human‑in‑the‑loop validation, RAG, tool‑use patterns) used in production environments.
• FinOps experience: cloud cost attribution, workload optimisation, and AI/LLM spend control.
• Familiarity with LLM gateway/router patterns for cost control, model routing, and observability of AI workloads.
• Clear communication skills and the ability to collaborate effectively with partner teams in a distributed environment.
• Experience using AI‑assisted development tools (e.g., GitHub Copilot, Cursor, ChatGPT, or similar tools) as part of your software development workflow

At EarnIn, we believe that the best way to build a financial system that works for everyday people is by hiring a team that represents our diverse community. Our team is diverse not only in background and experience but also in perspective. We celebrate our diversity and strive to create a culture of belonging. EarnIn does not unlawfully discriminate based on race, colour, 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 our hiring managers or HR team.