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About This Role
Overview
Are you a Software Engineer already at the forefront of agentic AI development — someone who uses agents to build software today and wants to build the platform that brings those capabilities to every developer at Microsoft? Do you have strong opinions about what great agentic tooling looks like, formed from real experience shipping with it? Do you want to dogfood the very platform you're building and have your own productivity transformed by it? If so, we'd love to talk with you about this opportunity!
Our AI team is a part of the larger ES365 (Microsoft 365 Engineering Systems) team — and we own the agentic engineering platform being adopted across all of Microsoft. ES365 owns the tools and systems used by thousands of Microsoft developers who innovate across the company's largest codebases, from source control and check\-in experience to build, validation, and deployment automation. This gives us a unique position to define what AI\-powered developer productivity looks like at Microsoft scale.
The ES365 AI team is 100% focused on pushing that frontier. We build the agentic platform itself and the experiences on top of it. The developers and codebase owners who use these tools are your customers, just down the hall — giving us a tight feedback loop and the domain expertise to move fast. For additional context, example workstreams have included AI\-assisted large\-scale codebase refactoring, automated package integrations, deep architectural Q\&A over codebases, and human\-in\-the\-loop directed code changes.
We're a growing team looking for a passionate and experienced Software Engineer. In this role, you'll help define and build the next generation of our agentic platform, orchestrating the latest AI models and harnesses in service of company\-wide developer productivity. You'll lead through excellent contributions to the ESAI codebase, advocate best practices for agentic development, and forge technical and mission\-based partnerships with other teams across Microsoft working on related problems.
If you are excited about AI's potential and want to be on the front lines of AI\-Powered developer efficiency at Microsoft, we want you in ES365 AI.
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.
Responsibilities
- Own and deliver complete features across the development lifecycle, including design, architecture, implementation, testability, debugging, shipping, and servicing.
- Use AI in your daily coding and advocate to the team and customers an evolving state\-of\-the\-art of how best to do this.
- Demonstrate resiliency to experiment and try multiple AI approaches that may not work — because no one has tried them before.
- Provide mentorship and coaching to engineers in, and beyond, your team.
- Write and review clean, well\-thought\-out code with an emphasis on quality, performance, simplicity, durability, scalability, and maintainability.
- Contribute positively to a culture where everyone can bring their full and authentic self and where we do our best work as a result.
Qualifications Required Qualifications:
- Bachelor'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 equivalent experience.
Other Requirements:
Ability to meet Microsoft, customer and/or government security screening requirements are required for this role. These requirements include but are not limited to the following specialized security screenings:
Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud background check upon hire/transfer and every two years thereafter.
Preferred Qualifications:
- Prior experience building with Agent SDKs, large language models (LLMs), prompt engineering, or AI orchestration frameworks (e.g., LangChain, Semantic Kernel, AutoGen, LlamaIndex, or similar).
- Familiarity with agentic AI development patterns — multi\-step reasoning, tool/function calling, retrieval\-augmented generation (RAG), and human\-in\-the\-loop workflows.
- Proven experience as a Software Engineer delivering large\-scale, production\-quality systems.
- Solid software engineering fundamentals: system design, algorithms, testing, debugging, and code review.
- Demonstrated ability to lead technical direction and mentor peers in a collaborative team environment.
- Comfort working in ambiguous, fast\-moving problem spaces where best practices are still being established.
- Hands\-on experience with AI\-powered developer tooling and coding assistants, such as:
- GitHub Copilot and Copilot Workspace — AI pair programming, CLI, and task\-oriented development
- Claude Code — agentic CLI for autonomous software engineering tasks
- OpenAI Codex / ChatGPT — LLM\-based code generation and explanation
- Cursor — AI\-native code editor with inline generation and multi\-file edits
- Prior experience using agentic plugins, agents, skills, hooks, etc.
- Experience dogfooding, evaluating, and forming opinions on emerging AI developer tools, and translating those insights into team\-wide best practices.
- Background in developer tooling, build systems, CI/CD pipelines, or engineering systems at scale.
\#CAP \#CAPHiring
Software Engineering IC5 \- The typical base pay range for this role across the U.S. is USD $142,800 \- $274,800 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 $188,000 \- $304,200 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.
Salary Context
This $142K-$304K range is above the 75th percentile for AI Software Engineer roles in our dataset (median: $183K across 194 roles with salary data).
Role Details
About This Role
AI Software Engineers build the applications and systems that AI models run inside. They own the API layers, data pipelines, frontend integrations, and infrastructure that turn a model into a product users interact with. Every AI company needs engineers who can build the software around the AI.
The challenge is building reliable systems around inherently unreliable components. Models are probabilistic. They'll give different answers to the same question. They hallucinate. They're slow. They're expensive. Your job is to build an application layer that handles all of this gracefully while delivering a product that users trust and enjoy.
Across the 3,708 AI roles we're tracking, AI Software Engineer positions make up 7% of the market. At Microsoft, this role fits into their broader AI and engineering organization.
AI Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.
What the Work Looks Like
A typical week includes: building API endpoints that serve model inference with caching and fallback logic, designing the data pipeline that feeds context to a RAG system, implementing streaming responses in the frontend, debugging a race condition in the async inference pipeline, and optimizing database queries for the vector search layer. It's full-stack engineering with AI at the center.
AI Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.
Skills Required
Full-stack engineering skills with AI integration experience. Python and TypeScript are the most common requirements. You'll need to understand API design, database architecture, and how to build reliable systems around probabilistic outputs. Experience with streaming, async processing, and caching patterns is increasingly important as real-time AI applications proliferate.
Knowledge of vector databases, embedding APIs, and LLM integration patterns (function calling, structured outputs, retry logic) differentiates AI software engineers from general software engineers. Understanding cost optimization (caching strategies, model routing, batched inference) is valuable since inference costs can dominate application economics.
Strong postings describe the product you'll be building, the AI integration patterns you'll work with, and the scale requirements. Look for companies that have existing AI features and need engineers to improve and expand them, not companies that are 'planning to add AI' someday.
Compensation Benchmarks
AI Software Engineer roles pay a median of $219,250 based on 424 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $230,000. Disclosed range: $142K to $304K.
Across all AI roles, the market median is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. For comparison, the highest-paying categories include AI Safety ($300,000) and Research Engineer ($280,000). By seniority level: Entry: $120,000; Mid: $200,000; Senior: $230,000; Director: $272,150; VP: $250,000.
Microsoft AI Hiring
Microsoft has 29 open AI roles right now. They're hiring across AI/ML Engineer, AI Software Engineer, Research Scientist, AI Product Manager. Positions span US, Redmond, WA, US, Dallas, TX, US. Compensation range: $143K - $304K.
Location Context
Across all AI roles, 14% (508 positions) offer remote work, while 3,180 require on-site attendance. Top AI hiring metros: New York (1,045 roles, $220,000 median); San Francisco (810 roles, $277,088 median); Los Angeles (397 roles, $215,000 median).
Career Path
Common paths into AI Software Engineer roles include Software Engineer, Full-Stack Developer, Backend Engineer.
From here, career progression typically leads toward Staff Engineer, AI Architect, Engineering Manager.
If you're a software engineer, you're already 80% there. Learn the AI integration patterns: RAG, streaming inference, function calling, structured outputs. Build a project that demonstrates you can wrap an AI model in a production-quality application with proper error handling, caching, and user experience. That's the portfolio piece that gets you hired.
What to Expect in Interviews
Technical screens look like standard software engineering interviews with an AI twist. Expect system design questions about building reliable applications around probabilistic models: handling streaming responses, implementing retry logic for API failures, and designing caching strategies for LLM outputs. Coding rounds test standard algorithms plus practical integration patterns like async processing and rate limiting.
When evaluating opportunities: Strong postings describe the product you'll be building, the AI integration patterns you'll work with, and the scale requirements. Look for companies that have existing AI features and need engineers to improve and expand them, not companies that are 'planning to add AI' someday.
AI Hiring Overview
The AI job market has 3,708 open positions tracked in our dataset. By seniority: 102 entry-level, 1,705 mid-level, 1,469 senior, and 432 leadership roles (Director, VP, C-Level). Remote roles make up 14% of the market (508 positions). The remaining 3,180 roles require on-site or hybrid attendance.
The market median for AI roles is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. Highest-paying categories: AI Safety ($300,000 median, 21 roles); Research Engineer ($280,000 median, 147 roles); AI Architect ($254,798 median, 67 roles).
AI Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.
The AI Job Market Today
The AI job market spans 3,708 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (2,605), Data Scientist (310), AI Software Engineer (259). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (102) are outnumbered by mid-level (1,705) and senior (1,469) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 432 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 14% of all AI roles (508 positions), with 3,180 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $217,500. Top-quartile roles start at $272,100, and the 90th percentile reaches $325,000. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $300,000 median, while Prompt Engineer roles sit at $140,000. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (1,890 postings), Aws (1,103 postings), Azure (877 postings), Rag (855 postings), Gcp (631 postings), Prompt Engineering (560 postings), Pytorch (545 postings), Claude (498 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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