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Microloft

Senior Software Engineer

Reposted 3 Days Ago
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Remote
Hiring Remotely in United States
120K-261K Annually
Senior level
Remote
Hiring Remotely in United States
120K-261K Annually
Senior level
Build AI-infused cybersecurity software and cloud services with customers, from discovery and architecture through production deployment, operations, and handoff. Develop secure agents, automation, integrations, and developer tooling; apply threat modeling, identity, authorization, privacy, and safe AI controls. Lead ambiguous technical workstreams, collaborate with customer and Microsoft engineering teams, evaluate and monitor AI systems, and convert engagement insights into reusable components, reference architectures, and product improvements.
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Overview

Microsoft Security Studio is seeking a Software Engineer to build AI-infused security solutions with customers at the intersection of AI, cloud, and cybersecurity.

Working in a Forward Deployed Engineering (FDE) model, you will embed with customer engineers, security teams, and Microsoft product teams to discover high-value problems, shape solutions, and deliver secure, production-ready software using Microsoft platforms, AI and agentic systems, and custom engineering where needed.

AI is central to how we engineer and what we build. You will apply AI-assisted practices across the development lifecycle and create intelligent security capabilities that reason over complex environments, automate workflows, assist defenders, and act safely on their behalf.

You will own the full lifecycle—from customer discovery, architecture, and success criteria through implementation, AI evaluation, deployment, operation, and a clean handoff of maintainable code and an operable solution.

You will also convert engagement insights into reusable assets, accelerators, patterns, and product improvements that extend the Studio’s impact.

This role offers the opportunity to

  • Build AI-infused security products and solutions with customers by working directly with customer engineers, security leaders, and Microsoft engineering teams on ambiguous, mission-critical problems.
  • Apply AI throughout the engineering lifecycle and agentic systems across security scenarios such as security operations, vulnerability discovery and remediation, secure software development, identity, governance, and AI security.
  • Move rapidly from problem discovery to prototype to production, using working software and measurable outcomes to drive decisions.
  • Build solutions across the Microsoft cloud, security, developer, data, and AI ecosystem while meeting customers where they are.
  • Convert customer-specific learning into reusable components, reference architectures, accelerators, and product improvements.

Responsibilities
  • Design and build AI-infused security software with customers, including cloud services, intelligent applications, security automation, agents, developer tooling, integrations, and distributed systems.
  • Embed with customer engineering and security teams to understand desired outcomes, architecture, threat models, data, and operational constraints, then translate ambiguity into executable engineering plans.
  • Co-develop in short, iterative cycles, demonstrating working software and using real-user feedback, evaluations, telemetry, and operational data to refine the solution and measure success.
  • Own production-quality delivery from prototyping and architecture through implementation, automated testing, CI/CD, infrastructure as code, deployment, observability, troubleshooting, documentation, operational readiness, and handoff.
  • Use AI-assisted engineering across the lifecycle and build agentic systems that safely access enterprise data and tools, with appropriate human review, identity, authorization, data boundaries, isolation, auditability, guardrails, and accountability.
  • Apply secure-by-design and privacy-by-design principles, including threat modeling, least privilege, secrets and identity management, data protection, dependency and vulnerability management, and secure operations.
  • Convert customer-specific learning into reusable components, accelerators, reference implementations, engineering patterns, paved paths, and actionable product feedback.
  • Lead significant technical workstreams by setting direction, decomposing ambiguous problems, making architecture decisions, managing dependencies, risks, and trade-offs, and communicating clearly with technical and senior stakeholders.
  • Collaborate in small multidisciplinary teams, learn rapidly, experiment responsibly, challenge assumptions constructively, and share knowledge across engagements.

Qualifications

Required Qualifications

  • Bachelor’s Degree in Computer Science or a related technical field and 4+ years of technical engineering experience coding in one or more languages such as C, C++, C#, Java, JavaScript, TypeScript, Go, Rust, or Python; or equivalent experience.
  • Demonstrated experience designing, building, testing, deploying, debugging, and operating substantial production software or cloud services.
  • Strong software-engineering fundamentals, including data structures, algorithms, APIs, distributed systems, cloud architecture, testing, reliability, and maintainable design.
  • Experience translating ambiguous, evolving customer or stakeholder needs into architecture, engineering plans, working software, and measurable outcomes.
  • Practical knowledge of secure software engineering, including authentication and authorization, identity, secrets management, threat modeling, data protection, secure dependencies, vulnerability remediation, and monitoring.
  • Ability to explain complex technical concepts, architecture decisions, trade-offs, and delivery risks to technical and nontechnical audiences.

Preferred Qualifications

  • Master’s Degree in Computer Science or a related technical field and 6+ years of technical engineering experience; or Bachelor’s Degree and 8+ years of technical engineering experience; or equivalent experience.
  • Strong hands-on experience building and operating AI- or LLM-based applications, agents, or developer systems, including orchestration, grounding/RAG, structured tool use, evaluation, observability, safety controls, and production monitoring.
  • Experience building agentic systems that interact with enterprise data, APIs, tools, or workflows, with attention to identity, authorization, auditability, data boundaries, and safe execution.
  • Experience using AI-assisted development and coding agents across the engineering lifecycle.
  • Experience building cybersecurity products or solutions in areas such as security operations, vulnerability management, identity, endpoint or cloud security, software supply-chain security, automation, or AI security.
  • Experience with cloud-native architecture, distributed systems, containers, infrastructure as code, CI/CD, observability, reliability engineering, and live-site operations.
  • Knowledge of AI security and security for AI, including prompt-injection defenses, sensitive-data handling, grounding controls, model or agent evaluation, responsible AI, and safe tool execution.
  • Demonstrated ability to move from customer problem → prototype → production solution → reusable engineering asset while balancing speed, quality, security, and maintainability.
  • Experience partnering with product engineering teams to turn customer scenarios and technical blockers into actionable requirements, prototypes, or validation evidence.
  • Ability to work effectively in small, high-ownership multidisciplinary teams and with senior customer engineering and security leaders while remaining deeply hands-on.
  • Willingness and ability to travel up to 25%.

Team and Benefits

Security Studio combines startup-like urgency, ownership, and experimentation with Microsoft’s engineering depth, product portfolio, and global customer reach.

Our engineers build with customers, not just for them, tackling difficult security and AI challenges and measuring success by durable customer outcomes.

We value deep engineering, customer empathy, responsible experimentation, security, operational excellence, and a learn-it-all mindset. Lessons from engagements become reusable tooling and patterns, while recurring product gaps inform improvements across Microsoft’s platforms.

 


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.

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