Interested in this AI Software Engineer role at AMD?
Apply Now →Skills & Technologies
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 ROLE
------------
AMD is seeking an experienced Embedded Software Engineer to help develop next\-generation Physical AI platforms powered by AMD Adaptive SoCs and Ryzen™ AI Embedded processors.
Working at the intersection of embedded software, computer vision, graphics, and edge AI, you will help bring intelligent robotics, industrial automation, autonomous systems, and smart vision applications to life. In partnership with AMD architecture, silicon, AI, and product teams, you will develop reference platforms, proof\-of\-concepts, and next\-generation solutions that showcase AMD technology in real\-world deployments.
Join a team shaping the future of Physical AI through adaptive computing. You'll work with industry\-leading Adaptive SoC, FPGA, and AI technologies, collaborate with world\-class engineers, and help enable the next generation of intelligent machines that are transforming industries worldwide.
THE PERSON
--------------
You are passionate about building robust embedded software and solving complex system\-level challenges. You enjoy working across hardware and software boundaries, bringing up new platforms, and developing innovative solutions in vision, graphics, and AI.
You thrive in collaborative environments, are naturally curious, and enjoy learning new technologies while partnering across engineering disciplines to deliver impactful products.
KEY RESPONSIBILITIES
------------------------
- Develop embedded C/C\+\+ software and Linux platform support (BSP/Yocto) for Physical AI platforms built on AMD Adaptive SoCs and Ryzen™ AI Embedded processors.
- Build and optimize computer vision and camera processing pipelines, including sensor drivers, MIPI CSI integration, ISP tuning, and image/video processing frameworks.
- Develop graphics and display software, including display pipeline bring\-up, GPU\-accelerated rendering, and visualization solutions for intelligent edge applications.
- Deploy and optimize edge AI inference models and runtime environments utilizing available NPU, GPU, and heterogeneous compute resources.
- Lead platform bring\-up, hardware/software integration, driver development, low\-level debugging, and system validation activities.
- Collaborate with AMD architecture, silicon, AI, and product engineering teams to influence future platform capabilities and improve the developer experience.
- Support performance optimization, system characterization, and software enablement for next\-generation AMD platforms.
- Investigate complex hardware and software issues, identify root causes, and deliver robust technical solutions.
- Contribute to reference platforms, proof\-of\-concepts, and customer\-facing demonstrations that showcase AMD technologies in robotics, industrial automation, computer vision, and Physical AI applications.
PREFERRED EXPERIENCE
------------------------
- Embedded software development using C/C\+\+, Python, automation, and AI model workflows.
- Experience with Embedded Linux, Yocto, BSP development, device drivers, RTOS, or bare\-metal software development.
- Experience with computer vision and camera pipelines, including MIPI CSI, ISP tuning, V4L2, OpenCV, or GStreamer.
- Experience with graphics and display software, including DisplayPort, MIPI DSI, display drivers, compositors, EGL, OpenGL, or Vulkan.
- Experience deploying and optimizing edge AI inference models using frameworks such as PyTorch, TensorFlow, ONNX, and related acceleration technologies.
- Experience with platform bring\-up, hardware/software integration, board bring\-up, and peripheral driver development.
- Experience working with high\-speed interfaces including PCIe, Ethernet, USB, DisplayPort, MIPI, SPI, I²C, UART, and GPIO.
- Familiarity with AMD Adaptive SoC, Ryzen AI Embedded, or similar heterogeneous computing platforms.
- Familiarity with FPGA concepts, RTL development, Verilog/VHDL, Vivado™, or Vitis™.
- Experience using hardware debugging tools such as JTAG, oscilloscopes, protocol analyzers, and logic analyzers.
- Familiarity with Git, CI/CD workflows, and modern software development practices.
- Experience with robotics, industrial automation, autonomous systems, ROS 2, machine vision, sensor fusion, or edge AI applications.
- Strong analytical, debugging, problem\-solving, and communication skills.
ACADEMIC CREDENTIALS
------------------------
- Bachelor's degree preferred in Electrical Engineering, Computer Engineering, Computer Science, Robotics Engineering, or a related technical discipline.
- Master's degree in a relevant technical field is desirable.
LOCATION
------------
San Jose, CA
----------------
*This role is not eligible for visa sponsorship.**\#LI\-Hybrid*
*\#LI\-DR2*
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 4,317 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 $218,500 based on 729 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $194,400.
Across all AI roles, the market median is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. For comparison, the highest-paying categories include AI Safety ($287,500) and Research Engineer ($272,100). By seniority level: Entry: $110,000; Mid: $194,400; Senior: $227,400; Director: $274,554; VP: $241,000.
AMD AI Hiring
AMD has 21 open AI roles right now. They're hiring across AI/ML Engineer, Data Scientist, AI Product Manager, AI Software Engineer. Positions span San Diego, CA, US, Austin, TX, US, San Jose, CA, US.
Location Context
Across all AI roles, 15% (635 positions) offer remote work, while 3,657 require on-site attendance. Top AI hiring metros: New York (1,650 roles, $220,000 median); San Francisco (1,335 roles, $265,000 median); Los Angeles (708 roles, $214,112 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 4,317 open positions tracked in our dataset. By seniority: 138 entry-level, 2,071 mid-level, 1,655 senior, and 453 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (635 positions). The remaining 3,657 roles require on-site or hybrid attendance.
The market median for AI roles is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. Highest-paying categories: AI Safety ($287,500 median, 34 roles); Research Engineer ($272,100 median, 227 roles); AI Engineering Manager ($244,000 median, 23 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 4,317 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (3,004), Data Scientist (345), AI Software Engineer (309). 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 (138) are outnumbered by mid-level (2,071) and senior (1,655) 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 453 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (635 positions), with 3,657 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 $215,000. Top-quartile roles start at $266,300, and the 90th percentile reaches $320,790. 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 $287,500 median, while Prompt Engineer roles sit at $145,000. 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 (2,249 postings), Aws (1,224 postings), Azure (938 postings), Rag (915 postings), Gcp (660 postings), Pytorch (640 postings), Prompt Engineering (624 postings), Kubernetes (559 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
Get Weekly AI Career Intelligence
Salary data, skills demand, and market signals from 16,000+ AI job postings. Every Monday.