header alt image test
Microloft Logo

Microloft

Senior Software Engineer

Posted 12 Days Ago
Be an Early Applicant
In-Office
Mountain View, CA, USA
120K-261K Annually
Senior level
In-Office
Mountain View, CA, USA
120K-261K Annually
Senior level
Build and maintain secure, reusable Azure infrastructure platforms using Terraform and programmatic IaC frameworks. Consult with engineering teams on cloud architecture, security, cost optimization, and governance. Develop AI agents, MCP integrations, self-service tooling, CI/CD pipelines, observability systems, and deployment automation. Support globally distributed, highly available environments, Kubernetes and AKS platforms, compliance remediation, and developer productivity initiatives while contributing to platform strategy and technical direction.
The summary above was generated by AI
Overview

Microsoft Ads 3rd Party Ads Solutions and Data Management Platforms is building the next innovative platform for AI-driven advertising. Our team empowers internal engineering teams through secure, scalable, and cost-effective cloud infrastructure solutions. We are reimagining the developer experience by using Infrastructure as Code (IaC), automation, and AI-driven interfaces to accelerate productivity and reduce operational complexity. 

We are looking for an Azure Platform Engineer who will help us create and evolve a foundational platform that enables teams across Ads to build with speed, security, and efficiency. This role blends cloud architecture consulting, Infrastructure as Code expertise, and AI tooling to deliver reusable and scalable patterns that reduce toil and promote innovation. 

As part of the Platform Engineering team, you will partner with engineering teams, architects, and product groups to design, implement, and evangelize cloud best practices, all while staying curious and open to trying new ideas. 

Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.  

Starting January 26, 2026, Microsoft AI (MAI) employees who live within a 50- mile commute of a designated Microsoft office in the U.S. or 25-mile commute of a non-U.S., country-specific location are expected to work from the office at least four days per week. This expectation is subject to local law and may vary by jurisdiction.


Responsibilities
  • Build and maintain secure-by-default, reusable Terraform and CDKTF/CDKTN modules to standardize and accelerate Azure infrastructure deployments. 
  • Consult with internal engineering teams to guide cloud architecture design, optimize for cost and security, and ensure alignment with platform standards. 
  • Develop automation and AI-driven interfaces that improve internal usability, accelerate onboarding, and unlock developer productivity. 
  • Build and maintain AI agents and MCP server integrations that automate operational work, and own them as production platform components with proper CI/CD, versioning, and evaluation. 
  • Drive security and compliance remediation across many repositories and teams, using automation and reusable patterns rather than manual effort. 
  • Own shared observability and deployment tooling, including managed Grafana, alert quality, and deployment automation. 
  • Design and implement scalable CI/CD pipelines and operational tooling. 
  • Write high-quality documentation and communicate complex technical concepts to diverse audiences in a clear, engaging way. 
  • Participate in platform strategy discussions and contribute to cross-team technical direction. 

Qualifications

Required Qualifications:

  • Bachelor's Degree in Computer Science or related technical field AND 4+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python
    • OR equivalent experience.

Preferred Qualifications:

  • Master's Degree in Computer Science or related technical field AND 6+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python
    • OR Bachelor's Degree in Computer Science or related technical field AND 8+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python
    • OR equivalent experience.
  • 4+ years of experience in Microsoft Azure and Terraform (or experience with AWS or GCP and a solid interest in Azure). 
  • Experience managing systems at scale—globally distributed, highly available, and real-time, 24/7 environments. 
  • Proficiency with Infrastructure as Code tools like Terraform, and with at least one programmatic IaC framework such as CDKTF, CDKTN, Pulumi, or Bicep. 
  • Minimum of 4 years of experience in programming or scripting with modern software development practices, including CI/CD pipelines.
  • Practical experience building or integrating AI agents—for example MCP servers, agent tooling, or automation built on LLMs—and a clear view of where automation is and is not appropriate. 
  • Excellent written and verbal communication skills, especially explaining technical concepts to non-specialist audiences. 
  • A growth mindset, openness to learning, and passion for trying new approaches to improve developer experiences. 
  • 6+ years of experience deploying and managing Azure infrastructure, especially globally distributed and highly available systems. 
  • Hands-on experience deploying Terraform on Azure, and experience migrating between Infrastructure as Code toolchains. 
  • Familiarity with CI/CD tools such as Azure DevOps or GitHub Actions. 
  • Experience building self-service tools and developer platforms for provisioning Azure infrastructure. 
  • Experience with Kubernetes and AKS, including admission policy and cluster platform services. 
  • Experience with observability tooling such as Grafana, Prometheus, or Azure Monitor, and querying telemetry with Kusto (KQL). 
  • Experience operating in a compliance-driven environment and driving remediation across teams you do not directly own. 
  • Solid understanding of cloud cost optimization, secure access control, and automated governance. 

#MicrosoftAI 


Software Engineering IC4 - The typical base pay range for this role across the U.S. is USD $119,800 - $234,700 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $160,200 - $261,000 per year.

Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:
https://careers.microsoft.com/us/en/us-corporate-pay


This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.



Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.

Similar Jobs at Microloft

11 Days Ago
In-Office
Mountain View, CA, USA
120K-261K Annually
Senior level
120K-261K Annually
Senior level
Automation
Designs, builds, secures, and operates Microsoft’s AdTech clean room infrastructure. Responsibilities include privacy-safe data collaboration, identity resolution, audience activation, measurement, secure data ingestion, access controls, encryption, compliance, observability, automation, reliability, and platform architecture. The role partners with engineering, marketing, privacy, security, data teams, and external partners to deliver scalable, regulated clean room environments.
Top Skills: AzureAzure Data FactoryAzure Event HubsAzure SynapseBicepCi/CdConfidential ComputingConsent ManagementCustomer Data PlatformsDatabricksIdentity GraphsIdentity ResolutionInfrastructure As CodeMicrosoft FabricPowershellPythonSparkSQLTerraform
11 Days Ago
In-Office or Remote
United States
102K-261K Annually
Senior level
102K-261K Annually
Senior level
Automation
Build and optimize distributed services supporting large-scale reinforcement learning, LLM post-training, and production AI workloads. Improve researcher and engineer iteration loops, debug model-hardware interactions, enhance performance and reliability, and develop expertise in ML systems, AI infrastructure, compute orchestration, GPU computing, inference, and distributed training. Responsibilities also include secure coding, architecture, deployment, observability, incident response, and on-call support.
Top Skills: CC#C++Cloud SoftwareContainersDistributed Training InfrastructureGpu ComputingJavaPost-TrainingPythonRayReinforcement LearningSglangSlimeVerlVllm
6 Days Ago
In-Office or Remote
3 Locations
143K-331K Annually
Senior level
143K-331K Annually
Senior level
Automation
Develop and lead production AI infrastructure across frameworks, runtimes, benchmarking, performance tooling, observability, and hardware platforms. Responsibilities include optimizing large language model training and inference, building automation, diagnosing cross-stack performance issues, defining technical architecture, driving platform improvements, collaborating across research and infrastructure teams, and mentoring engineers. The role spans senior and principal-level individual contributor responsibilities focused on scalable, reliable, and efficient AI systems.
Top Skills: Amd GpusAzureC++CudaMicrosoft SiliconNvidia GpusOnnx RuntimePythonPyTorchRocmTensorFlowTriton

What you need to know about the San Francisco Tech Scene

San Francisco and the surrounding Bay Area attracts more startup funding than any other region in the world. Home to Stanford University and UC Berkeley, leading VC firms and several of the world’s most valuable companies, the Bay Area is the place to go for anyone looking to make it big in the tech industry. That said, San Francisco has a lot to offer beyond technology thanks to a thriving art and music scene, excellent food and a short drive to several of the country’s most beautiful recreational areas.

Key Facts About San Francisco Tech

  • Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
  • Major Tech Employers: Google, Apple, Salesforce, Meta
  • Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
  • Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
  • Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
  • Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account