AI Design Automation Engineer

Amd

Confirmed live today High trust

Quick summary

Work type: On-site
Location: San Jose, CA
Salary: $200,000–$300,000 / yr
Posted: 46 days ago
Freshness: Confirmed live today
Closes: Sep 10, 2027
Nearby: 99+ roles within 25 mi

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $186k

This role $250k

$123k $319k

below market most similar roles pay here above market

This role pays more than 87% of similar roles. Most pay $152,150–$220,812 — the blue band above. At the midpoint, this role pays about $250k versus about $186k for comparable roles.

Based on 240 similar postings.

Employer

About Amd

AMD (Advanced Micro Devices) is a semiconductor company that develops high-performance processors, graphics cards, and adaptive computing solutions for gaming, data centers, and embedded markets. Industry: Semiconductors

Amd currently has 496 open roles on FindRole.

Listed pay typically runs $172,000–$258,000 across 496 roles with salary data.

Most-posted roles

View all roles at Amd

At a glance

TL;DR · AI Design Automation Engineer

Role Posting Log in to save

As an AI Design Automation Engineer within the AMD-AECG team, you will build next-generation AI-powered engineering platforms to help chip design teams interact with complex semiconductor design data. You will develop scalable software systems, data pipelines, knowledge graphs, and AI/LLM-driven capabilities, including retrieval-augmented generation and agentic workflows. Your daily work involves designing backend data pipelines, evolving data schemas, and tuning LLM components for accuracy and latency. You will utilize Python, graph databases, vector search systems, and relational data stores to process large volumes of engineering data. The role requires familiarity with RTL/HDL/Physical Design semantics, including SystemVerilog and Verilog. You will solve technical problems by translating data needs from architecture and verification teams into production-quality tools for designing CPUs, GPUs, and AI accelerators.

Skills

Python LLM Knowledge Graphs Vector Search Data Pipelines Backend Systems SystemVerilog Verilog TDD Graph Databases Hardware Design HDL

What you'll do

Design and maintain backend data pipelines to convert engineering data into structured, queryable formats.
Develop and evolve data schemas to support new engineering data types at production scale.
Build AI/LLM-based components to enable engineers to query data using natural language.
Diagnose and resolve reliability and performance issues in distributed batch-processing pipelines.
Implement new data pipelines to integrate additional engineering data domains onto the platform.
Tune LLM-based components for optimal accuracy, cost, and latency.
Execute a TDD-driven development workflow using version control and code review practices.
Translate data and workflow needs from architecture and design teams into platform capabilities.

What we're looking for

Bachelor's or Master's degree in Computer Science, Computer Engineering, Electrical Engineering, or a related field.
Experience building production-quality backend systems and large-scale data pipelines.
Experience developing AI/LLM-based solutions such as retrieval systems, knowledge graphs, and agentic workflows.
Strong Python engineering background with rigorous testing discipline (preferred).
Experience with graph databases and/or vector search systems (preferred).
Experience with LLM-based/agentic systems including RAG and agent orchestration (preferred).
Familiarity with RTL/HDL/Physical Design semantics and hardware design source toolchains (preferred).
Experience with time-series/relational data stores and reasoning about consistency (preferred).

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