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About This Role
Overview:
WHAT YOU DO AT AMD CHANGES EVERYTHING
At AMD, our mission is to build great products that accelerate next\-generation computing experiences—from AI and data centers, to PCs, gaming and embedded systems. Grounded in a culture of innovation and collaboration, we believe real progress comes from bold ideas, human ingenuity and a shared passion to create something extraordinary. When you join AMD, you’ll discover the real differentiator is our culture. We push the limits of innovation to solve the world’s most important challenges—striving for execution excellence, while being direct, humble, collaborative, and inclusive of diverse perspectives. Join us as we shape the future of AI and beyond. Together, we advance your career.
Responsibilities:
THE GROUP:
AI is defining the next era of computing, and this is just the beginning. We see the benefits of AI every day—enabling medical research, curbing credit card fraud, reducing congestion in cities, or simply making life easier.
In the ever\-evolving landscape of artificial intelligence, we are a powerhouse – a cutting\-edge 'AI Software Solutions Team'. Specialized in AI optimization, fine\-tuning large language models to unlock unprecedented Generative AI efficiency. Our expertise extends beyond the hardware realm, encrompassing 3P enablement, where we develop custom AI Software Solutions for Industry leading AI customers. Are you excited to work with one of Top 1% of the AI companies in the world? THE ROLE:
Would you like to be part of a world class team enabling software for world class datacenters and the mightiest supercomputers? AMD is searching for talented and highly motivated AI Software Engineers to join our team of developers pushing the boundaries of efficiency and performance to enable and optimize the software ecosystem for the next generation of GPU computational accelerators. Our team has an unparalleled perspective of the AI landscape. We work with the industry’s most sophisticated clients to help them leverage the latest hardware capabilities for their AI use cases. As part of our team, you will be among the first in the world to combine the newest hardware with the industry’s latest applications, libraries, frameworks, and SDKs to push the limits of innovation and solve the world’s most complex challenges. Minimum 4 years of experience required. THE PERSON:
We are looking for a highly motivated and skilled AI Software Engineer to join our team. You will work with a team of Software Engineers to enable DL models, libraries, and applications for Instinct GPUs in both on\-prem and Cloud environments. Candidates should be strong in Python and/or C\+\+. Candidates should also have experience analyzing and optimizing the performance of AI software and understand hardware bottlenecks and harness performance to hit close to roofline. Must be self\-motivated and possess the ability to work well within a team environment. KEY QUALIFICATIONS:* Strong programming skills in C\+\+ and Python
- Strong development experience is at least one major DL framework such as Pytorch or Tensorflow in inference, fine tuning and/or training
- MS with years of related experience or PhD with years of related experience in Computer Science or Computer Engineering or related equivalent.
- Experience developing software and system\-level performance optimizations with a solid architecture understanding in GPUs a plus
- Experience with open\-source software development including collaboration with community maintainers and submitting contributions is a plus
- Publications in reputed peer\-reviewed ML conferences/journals a plus
- Excellent analytical and problem\-solving skills root\-causing/addressing performance issues.
- Ability to work independently and as part of a team.
- Willingness to learn skills, tools, and methods to advance the quality, consistency, and timeliness of AMD software products.
PREFERRED EXPERIENCE:* Expertise in profiling tools across the AI SW Stack (Torchprofiler, RocM profiler, Vtune, Nsight)
- Experience in implementing and optimizing parallel methods on GPU accelerators (NCCL/RCCL, OpenMP, MPI)
- Performance analysis skills for both CPU and GPU
- Experience with Singularity, Docker, and/or Kubernetes.
- Experience providing clear and timely communication related to status and other key aspects of the project to leadership team.
\#LI\-RL1This role is not eligible for visa sponsorship.
Qualifications:
*Benefits offered are described:* AMD benefits at a glance. *AMD does not accept unsolicited resumes from headhunters, recruitment agencies, or fee\-based recruitment services. AMD and its subsidiaries are equal opportunity, inclusive employers and will consider all applicants without regard to age, ancestry, color, marital status, medical condition, mental or physical disability, national origin, race, religion, political and/or third\-party affiliation, sex, pregnancy, sexual orientation, gender identity, military or veteran status, or any other characteristic protected by law. We encourage applications from all qualified candidates and will accommodate applicants’ needs under the respective laws throughout all stages of the recruitment and selection process.* *AMD may use Artificial Intelligence to help screen, assess or select applicants for this position. AMD’s “Responsible AI Policy” is available* *here.* *This posting is for an existing vacancy.*
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 3,823 AI roles we're tracking, AI Software Engineer positions make up 7% of the market. At AMD, 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 $232,000 based on 797 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $165,000.
Across all AI roles, the market median is $200,100. Top-quartile compensation starts at $253,500. The 90th percentile reaches $307,500. For comparison, the highest-paying categories include AI Engineering Manager ($275,000) and AI Safety ($274,200). By seniority level: Entry: $97,880; Mid: $165,000; Senior: $227,400; Director: $247,800; VP: $250,000.
AMD AI Hiring
AMD has 6 open AI roles right now. They're hiring across AI/ML Engineer, AI Software Engineer. Positions span San Jose, CA, US, Austin, TX, US, Santa Clara, CA, US. Compensation range: $244K - $244K.
Location Context
Across all AI roles, 15% (590 positions) offer remote work, while 3,217 require on-site attendance. Top AI hiring metros: New York (2,643 roles, $211,000 median); San Francisco (2,168 roles, $253,000 median); Los Angeles (1,792 roles, $191,580 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 3,823 open positions tracked in our dataset. By seniority: 112 entry-level, 1,798 mid-level, 1,516 senior, and 397 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (590 positions). The remaining 3,217 roles require on-site or hybrid attendance.
The market median for AI roles is $200,100. Top-quartile compensation starts at $253,500. The 90th percentile reaches $307,500. Highest-paying categories: AI Engineering Manager ($275,000 median, 41 roles); AI Safety ($274,200 median, 55 roles); Research Engineer ($260,000 median, 434 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 3,823 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (2,629), Data Scientist (322), AI Software Engineer (279). 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 (112) are outnumbered by mid-level (1,798) and senior (1,516) 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 397 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (590 positions), with 3,217 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 $200,100. Top-quartile roles start at $253,500, and the 90th percentile reaches $307,500. 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 Engineering Manager roles lead at $275,000 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 (1,979 postings), Aws (1,190 postings), Azure (899 postings), Rag (839 postings), Gcp (726 postings), Pytorch (595 postings), Prompt Engineering (595 postings), Claude (540 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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