Forward Deployment Engineer (Hardware / EDA)
llmda.aiJob Title
Forward Deployment Engineer (Hardware / EDA)
Role Summary
Customer-facing engineering role that deploys and integrates llmda.ai's Generative AI platform into semiconductor design and verification workflows. Acts as a technical consultant, deployment lead, and feedback channel between customers and internal ML/product teams.
Primary mission: enable customers to adopt AI-driven EDA capabilities to reduce design iterations and accelerate time-to-silicon.
Experience Level
Mid-level (expectation: 5+ years of hands-on experience in front-end semiconductor design or verification).
Responsibilities
Lead technical deployment, integrate tools into customer workflows, and ensure successful adoption while feeding field insights back to product and ML teams.
- Lead technical deployment of llmda.ai products for PoCs and enterprise rollouts.
- Analyze customers' hardware design and verification challenges and apply LLM/GenAI tools to automate tasks.
- Map existing design workflows to AI-native capabilities and demonstrate efficiency improvements.
- Collect and translate customer feedback and field data into actionable requirements for ML and product teams.
- Train and enable customer engineering teams on AI-assisted EDA usage and hardware-specific prompt engineering.
- Work closely with customers to troubleshoot integration, verification, and deployment issues.
Requirements
Must-have technical skills and customer-facing experience for successful execution of the role.
- 5+ years of hands-on experience in front-end semiconductor design or verification (specification to synthesis).
- Practical experience with or strong understanding of Large Language Models and Generative AI applied to hardware engineering tasks.
- Deep proficiency in SystemVerilog, Verilog, and RTL design.
- Strong understanding of verification methodologies such as UVM, formal verification, coverage-driven verification, and simulation debugging.
- Customer-facing technical experience (FAE, CAE, Deployment Engineer, or equivalent) in EDA or semiconductor IP domains.
- Scripting and automation skills in Python, Tcl, Perl or similar languages used to integrate and automate tool flows.
- Ability to operate in a fast-moving startup environment and iterate quickly on customer deployments.
Nice-to-have: hands-on prompt engineering for hardware tasks, prior experience deploying AI tools in engineering workflows, and familiarity with architectural exploration or automated debugging use cases.
Education Requirements
Not specified.
About the Company
Company: llmda.ai
Headquarters: Santa Clara, CA, USA
llmda.ai builds a Generative AI-based semiconductor design platform that integrates agentic AI and semantic engines to automate hardware and chip design processes, reduce re-spins, and identify design issues early. The company focuses on AI-driven workflow optimization and customer deployments for front-end semiconductor design and verification.
