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职位Cadence

Sr Principal Software Engineer

Cadence

Sr Principal Software Engineer

Cadence

NOIDA; BANGALORE

·

On-site

·

Full-time

·

1d ago

At Cadence, we hire and develop leaders and innovators who want to make an impact on the world of technology.

About Us

Chips are at the center of today's tech-driven world. But how we design and verify them has not fundamentally changed in decades, while their complexity and specialization have skyrocketed due to increasing performance demands from AI. We are a dynamic, fast-moving team of software developers, ML scientists, and research-minded engineers on a mission to change that.

Operating with the agility of a startup but backed by industry-leading verification technologies, we are part of the System Verification Group (SVG). Our charter is to develop state-of-the-art EDA software and hardware platforms (including Xcelium, Jasper, Palladium, Protium, and Helium) and supercharge them with cutting-edge AI, automation, and advanced data-driven workflows.

About This Role:

Cadence Design Systems is the leading provider of design automation tools for electronic and intelligent systems design. The ML / Software Engineer – Chip Stack Super Agent Team will be responsible for designing, implementing, and evaluating AI agents that enhance productivity across the semiconductor design lifecycle. This engineer will contribute to the development of robust agent infrastructure, evaluation systems, and production-grade AI capabilities integrated within Cadence’s electronic design automation (EDA) ecosystem.

The role focuses on building reliable, scalable agentic systems that operate within complex engineering workflows. The ideal candidate combines strong software engineering fundamentals with practical experience in ML systems and agent infrastructure, enabling deployment of high-impact AI solutions in production environments.

Responsibilities

  • Design and implement scalable infrastructure for AI agents operating within Cadence’s Chip Stack Super Agent ecosystem.
  • Build robust evaluation frameworks to measure agent performance, reliability, and alignment with engineering workflows.
  • Develop data pipelines, retrieval systems, and context-engineering strategies to support consistent and grounded agent behavior.
  • Contribute to continuous integration, automated testing, and observability systems to ensure production-quality deployment of AI-enabled systems.
  • Optimize system performance across latency, cost, reliability, and scalability dimensions.

Required Qualifications

  • Bachelors/MS/PhD in Computer Science, Computer Engineering, or related technical field with 15+ Years of relevant experience in software development.
  • Strong software engineering fundamentals, including design, refactoring, debugging, and testing of complex distributed systems. Demonstrated experience building production-quality systems.
  • Understanding of large language models (LLMs) and practical considerations for deploying them in real-world systems (latency, cost, reliability, monitoring).
  • Experience designing evaluation frameworks for AI systems, including benchmarking, regression testing, and failure analysis.

Skills of Interest

  • Agent architecture: Experience with reason–act loops, planning/evaluation/self-correction patterns, tool/function calling, persistent memory systems, and structured outputs.
  • LLM engineering: Familiarity with frontier LLMs and trade-offs across model families; experience with prompt engineering, context management, and alignment techniques.
  • Retrieval and data systems: Understanding of RAG pipelines, embeddings, indexing strategies, chunking methodologies, and grounding techniques.
  • Infrastructure and observability: Experience building logging, tracing, monitoring, and evaluation systems for ML/AI applications.
  • AI-assisted development workflows: Leveraging AI tools to enhance engineering productivity and code quality.
  • Interest in semiconductor design, EDA workflows, and high-performance computing environments.

Our Culture

  • Challenge the status quo:

We are innovators who challenge industry norms and push forward our vision of how silicon should be built.

  • Strong opinions, loosely held:

We are low on ego, but high on collaboration. We are okay to be wrong and are always open to learning.

  • Ship fast, ship quality:

We ruthlessly prioritize what matters. We build at lightning speed, but never compromise on the high standards required by the semiconductor industry.

  • Proud of our craft:

Attention to detail is in our DNA. We take pride in what we build and go the extra mile to ensure an exceptional experience for our users.

Behavioral skills required:

  • Must possess strong written, verbal and presentation skills.
  • Good communication and interpersonal skills, demonstrate teamwork and collaboration skills.
  • Ability to establish a close working relationship with both customer peers and management.
  • Explore what’s possible to get the job done, including creative use of unconventional solutions
  • Work effectively across functions and geographies
  • Push to raise the bar while always operating with integrity

We’re doing work that matters. Help us solve what others can’t.

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关于Cadence

Cadence

Cadence

Public

Cadence Design Systems, Inc. is an American multinational technology and computational software company headquartered in San Jose, California.

5,001-10,000

员工数

San Jose

总部位置

$8.5B

企业估值

评价

4.0

10条评价

工作生活平衡

4.2

薪酬

2.8

企业文化

4.1

职业发展

3.2

管理层

3.4

72%

推荐给朋友

优点

Good work-life balance and flexible hours

Supportive and collaborative team environment

Good benefits and stable company

缺点

Below market compensation and pay

Limited growth and advancement opportunities

Heavy workload and long hours during peak times

薪资范围

66个数据点

Junior/L3

Junior/L3 · Data Analyst

1份报告

$91,103

年薪总额

基本工资

$85,276

股票

-

奖金

$5,827

$59,612

$139,984

面试经验

1次面试

难度

3.0

/ 5

时长

14-28周

面试流程

1

Application Review

2

Recruiter Screen

3

Technical Phone Screen

4

Onsite/Virtual Interviews

5

Final Decision

常见问题

Technical Knowledge

Behavioral/STAR

Past Experience

Problem Solving