Software Development Engineer Infra 2

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

As a Software Development Engineer 2 – Infra, 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.

• 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.

• 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

• 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

• 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

• 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

• 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

• 3–6 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

• 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

• 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

• 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
  

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.