Salesforce

Software Engineering MTS

Salesforce$117K — $176K *
Information Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • 1+ years of experience in cloud infrastructure engineering and continuous deployment.
  • Hands-on experience with Kubernetes for deployment, troubleshooting, and automation.
  • Proficiency in Golang and/or Python for building services or automation tools.
  • Familiarity with GitOps tools like Flux or Argo CD and infrastructure-as-code frameworks such as Pulumi or Terraform.
  • Demonstrated cognitive and practical use of AI tools for enhancing engineering productivity.
  • Strong communication and collaboration skills in a fast-paced team environment.

Responsibilities

  • Build and maintain automation tools in Go and Python for managing Kubernetes clusters across multiple cloud platforms.
  • Contribute to continuous deployment pipelines with GitOps tooling to ensure safe and repeatable releases.
  • Participate in automation initiatives such as cluster management, upgrades, and observability enhancements.
  • Collaborate with SRE, security, and product teams to deliver self-service capabilities that minimize manual work.
  • Utilize AI tools daily to enhance productivity and develop an agentic mindset for automating repetitive tasks.
  • Engage in design and code reviews, writing thorough technical documentation to develop cloud-native expertise.
  • Participate in on-call rotations to improve platform operations and learn from incidents.

Benefits

  • Comprehensive support for work-life balance.
  • Access to resources that promote personal and professional development.
  • AI tools provided to amplify productivity in engineering work.
  • Opportunities to influence the future of AI technology and cloud infrastructure.
Full Job Description
To get the best candidate experience, please consider applying for a maximum of 3 roles within 12 months to ensure you are not duplicating efforts.

Job Category
Software Engineering

Job Details

The Software Engineer (MTS) role is part of our Platform Engineering team within the Cloud Infrastructure organization. Platform Engineering is made up of platform engineers, SREs, and DevOps specialists who design, build, and operate the internal developer platform powering hundreds of Kubernetes clusters across AWS, Azure, GCP, and OCI. Whether we are automating cluster lifecycle management, hardening our GitOps delivery pipelines, or embedding AI into our daily engineering workflows, we strive to give every product team a fast, secure, and reliable path to production.

We are looking for a Member of Technical Staff to grow with our multi-cloud platform. You'll build and operate core platform services in Go and Python, contribute to our GitOps and continuous deployment pipelines, and learn to operate Kubernetes at scale - all while developing an **agentic mindset** and becoming an **AI amplifier** who multiplies your own output with AI-assisted engineering practices from day one.

### What You'll Actually Be Doing

Success will be measured by your growing contributions to the reliability, scalability, and developer experience of the platform services our team builds and operates across our multi-cloud Kubernetes fleet.

- Build and maintain platform services and automation in Go and Python that help manage Kubernetes clusters across AWS, Azure, GCP, and OCI.

- Contribute to continuous deployment pipelines using GitOps tooling (Flux, Argo CD) and infrastructure-as-code frameworks (Pulumi, Terraform) to enable safe, repeatable releases.

- Take part in fleet initiatives such as cluster lifecycle automation, upgrades, policy enforcement, and observability improvements, with guidance from senior engineers.

- Partner with SRE, security, and product engineering teams to understand their needs and help deliver self-service platform capabilities that reduce toil.

- Be an **AI amplifier**: use AI tooling in your everyday engineering workflows - agentic coding assistants (e.g., Claude Code) for development, code review, automation, and operational runbooks - to force-multiply your output as you ramp.

- Develop an **agentic mindset**: learn to spot repetitive operational work and propose agent-driven or AI-augmented automations that reduce manual effort.

- Participate in design reviews and code reviews, write clear technical documentation, and grow your platform and cloud-native expertise.

- Join on-call rotations as you ramp and help improve the operational posture of the platform through automation and post-incident learning.

### You're Our Person If...

- 1+ years of professional experience in cloud infrastructure engineering and continuous deployment.

- Hands-on Kubernetes experience - deploying, troubleshooting, and automating workloads or clusters (networking, scaling, upgrades).

- Good programming skills in Golang and/or Python, with experience building services, CLIs, or automation tooling.

- Multi-cloud exposure, primarily AWS, with a working understanding of core compute, networking, IAM, and managed Kubernetes services.

- Familiarity with GitOps using Flux or Argo CD, and infrastructure-as-code with Pulumi (or comparable tooling such as Terraform).

- Demonstrated AI literacy and an emerging **agentic mindset** - you actively use AI tools in your daily engineering work (code generation, debugging, documentation, automation) and can speak to how AI has amplified your output.

- Strong communication and collaboration skills, and an eagerness to learn and grow within a fast-moving platform team.

### Even Better If...

- Hands-on experience with Claude Code or other agentic coding tools - building agentic workflows, custom commands, or MCP integrations is a strong plus; any track record of being an AI amplifier stands out even more.

- Experience with GCP, OCI, or Azure beyond AWS, especially managing Kubernetes (GKE, OKE, AKS) across providers.

- Exposure to compliance-driven environments (FedRAMP, SOC 2) and sound security and change-management practices.

- Familiarity with policy-as-code (Kyverno, OPA/Gatekeeper), supply-chain security (cosign, SBOM), or artifact/registry governance.

- Exposure to internal developer platforms (IDPs), platform APIs, or developer experience tooling.

- Contributions to open-source cloud-native projects (CNCF ecosystem).

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Market Cap
$130.4 billion
Industry
Net Income
$4 billion
Founded
2000
5 Year Trend
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