Software Development Engineer Infra - 1

About the Role

At Cashfree, infrastructure is not just about running servers — it is a software platform that powers our engineering organization.

As a Software Development Engineer Infra - 1, you will build the systems, platforms, automation, and developer tools that enable hundreds of engineers to build and operate products reliably at scale.

This is a hands-on engineering role at the intersection of software engineering, distributed systems, cloud infrastructure, Kubernetes, reliability, security, developer productivity, and AI.

You will design and build production software — APIs, backend services, controllers, CLI tools, automation frameworks, infrastructure abstractions, internal developer platforms, and AI-powered engineering tools.

What You Will Build

AI-powered tools for troubleshooting, automation, developer productivity, and infrastructure operations

Internal developer platforms and self-service infrastructure

Infrastructure APIs, control planes, and automation

Kubernetes operators and infrastructure abstractions

Deployment, provisioning, and environment orchestration

Production debugging, observability, and incident-response tools

Security, governance, and cost-optimization automation

The goal is to make infrastructure self-service, reliable, secure, efficient, and increasingly intelligent.

Core Responsibilities

1. Build Internal Infrastructure Platforms

Build APIs, services, CLIs, and tools that simplify infrastructure consumption for engineering teams

Develop self-service workflows for service onboarding, deployments, environments, and infrastructure

Create reusable abstractions over cloud and Kubernetes

Build AI-assisted developer and infrastructure workflows that reduce operational effort and improve engineering productivity

Own platform features end-to-end from design to production

2. Build Cloud & Kubernetes Infrastructure

Build reusable Terraform/Pulumi modules and infrastructure frameworks

Develop Kubernetes operators, controllers, and platform components

Design highly available multi-AZ and multi-region infrastructure

Automate provisioning, scaling, failover, and infrastructure lifecycle management

Explore AI-driven automation for infrastructure provisioning, optimization, and operational decision-making

3. Engineer Reliability & Production Systems

Design systems for availability, failure isolation, graceful degradation, and automated recovery

Define and improve SLOs, SLIs, error budgets, and reliability metrics

Build observability, diagnostics, and production troubleshooting capabilities

Build AI-assisted incident detection, triage, root-cause analysis, and remediation workflows

Drive improvements to MTTR, capacity, performance, and operational toil

4. Build Secure & Efficient Infrastructure

Build IAM, secrets management, policy, and compliance automation

Embed security and governance controls into infrastructure workflows

Build tooling to identify infrastructure waste and automate resource optimization

Explore AI-assisted detection of security, configuration, and cost anomalies

Balance cost, performance, reliability, and developer productivity

5. Solve Complex Infrastructure Problems

Investigate and solve challenging problems across distributed systems, networking, Kubernetes, and cloud infrastructure

Turn recurring operational problems into scalable engineering solutions

Identify opportunities to apply AI/LLMs to automate complex engineering workflows and reduce manual operations

Work closely with product engineering and security teams to design platform capabilities

Take ownership of systems through design, implementation, deployment, and production operations

Job Requirements

Software Engineering

0-1 years of experience in software engineering, backend engineering, platform engineering, SRE, or a similar role

Strong programming skills in Go, Python, Java, Rust, or a similar language

Strong understanding of software design, APIs, concurrency, data structures, and distributed systems

Experience building and operating production-grade services, tools, or automation

Strong debugging and problem-solving skills

Cloud & Infrastructure

Strong understanding of Linux, networking, cloud infrastructure, and distributed systems

Hands-on experience with AWS, GCP, or Azure

Experience with infrastructure automation and Infrastructure as Code

Strong understanding of Kubernetes and containerized workloads

Experience with Terraform, Pulumi, OpenTofu, or similar tools

Reliability & Security

Understanding of SLOs, SLIs, observability, scalability, and failure recovery

Experience with tools such as Prometheus, Grafana, Datadog, OpenTelemetry, or equivalent

Understanding of IAM, secrets management, authentication, authorization, and least privilege

Experience with Kubernetes operators/controllers, GitOps, Vault, policy-as-code, or cloud cost optimization is a plus

AI & Automation — Nice to Have

Experience building applications or internal tools using LLMs, AI agents, or AI APIs

Understanding of LLM-based automation, tool calling, RAG, or agentic workflows

Experience integrating AI into developer productivity, observability, incident management, or infrastructure workflows

Familiarity with MCP or similar approaches for connecting AI systems to engineering tools and infrastructure is a plus

What We Value

We look for engineers who build instead of manually operate, automate repetitive work, think in APIs and abstractions, design for failure and scale, and take ownership of systems end-to-end.

We also value engineers who are curious about using AI to fundamentally improve how infrastructure is built, operated, and debugged.

Build the platform. Automate the work. Make every engineer faster.