Full-Stack AI Engineer
Posted yesterday
The role in short
Embed with semiconductor customers to integrate and refine agentic AI workflows for chip design and verification.
About ChipAgents
ChipAgents is redefining the future of chip design and verification with agentic AI workflows. Our platform leverages cutting-edge generative AI to assist engineers in RTL design, simulation, and verification, dramatically accelerating chip development. Founded by experts in AI and semiconductor engineering, we partner with top semiconductor firms, cloud providers, and innovative startups to build intelligent AI agents. The company is a Series A company backed by tier-1 VC firms. ChipAgents is deployed in production to companies that have shipped 16B chips.
Position Overview
We are looking for multiple Full-Stack AI Engineers with a strong Computer Science foundation to work closely with engineering teams at some of the world's leading chip companies. You'll be part of a cross-functional mission to create forward-looking agentic AI technologies, help customers integrate ChipAgents into their workflows, deliver real-world impact, and continuously improve our agentic AI platform based on field feedback. This is a deeply technical, customer-facing role ideal for someone excited to get out of the lab, visit customers, and solve practical problems with real usage data.
Key Responsibilities
- Own the technical success of ChipAgents deployments from start to finish: onboarding, integration, scaling, and feedback.
- Interface directly with customer engineering teams to understand their workflows and identify high-leverage opportunities for AI automation.
- Prototype and refine full-stack solutions—from backend models to frontend experiences—that embed agentic AI into EDA workflows.
- Collaborate with our core engineering team to improve models, tooling, and infrastructure based on field insights.
- Create internal and customer-facing resources (docs, tutorials, dashboards) that scale our support and enable rapid adoption.
- Stay hands-on with code: contribute to infrastructure, prompt engineering, workflow orchestration, and feedback-driven improvement.
Qualifications
- B.S. or M.S. in Computer Science or a related field.
- Experience building full-stack software, with strong fundamentals in software engineering and machine learning.
- Familiarity with modern ML workflows (e.g., Python, PyTorch, LLMs, etc.) and frontend development tools (e.g., TypeScript, JavaScript).
- Interest in electronic design automation (EDA), RTL, or hardware-software co-design (prior exposure is a plus, but not required).
- Excellent communication skills and comfort working directly with customer engineering teams.
- Willingness to travel for on-site customer visits and deep integration work.
- A self-starter who thrives in a fast-paced, mission-driven startup environment.
Why Join Us
- Shape the future of how AI accelerates chip design and verification.
- Work directly with the world's leading semiconductor and AI hardware companies.
- Be part of a high-impact, mission-driven team.
What we offer
- $150K/yr – $350K/yr + Offers Equity. We are open to discuss above-scale compensation with exceptional candidates on a case-by-case basis.
- Unlimited PTO and full benefits (medical, vision, dental, 401k).
- Two engineering-centric offices with free parking, private gym, and free lunch, drinks and snacks.
Prep for this interview
4 questions likely to come up at ChipAgents, each matched to a line in this posting.
- 1Coding
They wrote: “Familiarity with modern ML workflows (e.g., Python, PyTorch, LLMs, etc.) and frontend development tools (e.g., TypeScript, JavaScript).”
Here's a CSV export from a customer. Write a script that cleans it and loads it into our API.
How to answer
Why they ask: Very close to real FDE work. They watch how you handle bad rows and failures.
- Read with a proper CSV parser; check the header first
- Validate each row and collect errors, not crash on the first one
- Send in batches with retries and a clear report at the end
- Write one or two quick tests for the parsing
Tip: Talk through edge cases out loud: encodings, missing fields, duplicates, rate limits.
- 2Integrations and APIs
They wrote: “Own the technical success of ChipAgents deployments from start to finish: onboarding, integration, scaling, and feedback.”
Walk me through connecting our product to a customer's internal system that has no documentation.
How to answer
Why they ask: This happens weekly in the job. They want a calm, step-by-step method.
- Find who owns the system and get read access to a test environment
- Watch real traffic or logs to learn the data shapes
- Build a thin adapter with logging around every call
- Agree on how failures get reported, and who fixes what
Tip: Talk about finding the owner of the system first. The code is the easy part.
- 3LLMs, RAG and agents
They wrote: “Prototype and refine full-stack solutions—from backend models to frontend experiences—that embed agentic AI into EDA workflows.”
Support says the AI assistant “is wrong sometimes.” How do you make that something you can fix?
How to answer
Why they ask: Customers describe AI problems in feelings. They want to see you turn that into a number.
- Collect real failures from logs and from the support team
- Sort them: wrong document found, right document but wrong answer, or the question wasn't answerable
- Build a test set from them and measure today's error rate
- Fix the biggest group first and show the number moving
Tip: Ask for ten real bad examples before you change anything.
- 4Travel
They wrote: “Willingness to travel for on-site customer visits and deep integration work.”
How do you handle being on the road with customers for weeks at a time?
How to answer
Why they ask: Many FDE roles involve regular travel. They check you know what you're signing up for.
- Your past travel or on-site experience
- How you stay productive away from the team
- What travel level works for you, said plainly
Tip: Be honest about what works for you. A mismatch here hurts both sides later.
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