
Cognichip is an AI-first company revolutionizing semiconductor design with its Artificial Chip Intelligence (ACI)® platform. ACI® is the world's first physics-informed foundation AI model tailored…

Cognichip is an AI-first company revolutionizing semiconductor design with its Artificial Chip Intelligence (ACI)® platform. ACI® is the world's first physics-informed foundation AI model tailored…
Founded: 2024
Mission: Use AI (ACI®) to radically speed and reduce effort in chip design
Total disclosed funding: $93M
Recent round: $60M Series A led by Seligman Ventures (Apr 1, 2026)
Headcount (reported): 73
Semiconductor chip design automation and optimization using generative and physics-informed AI.
2024
DeepTech
$33M
Emergence from stealth with $33M seed
$60M
Participation from Lip-Bu Tan; Umesh Padval (Seligman) and Lip-Bu Tan join board
“Includes venture firms with domain-focused deep-tech investors and participation from industry executive Lip-Bu Tan”
Job Summary:
We are seeking a Staff Agentic AI Engineer to lead the architecture, implementation, and
production deployment of advanced agentic AI systems.
In this role, you will serve as a technical authority for multi-agent systems across Cognichip,
driving long-horizon autonomous workflows that integrate proprietary models, semiconductor
design tools, and cloud infrastructure. You will design systems that reason across multiple
steps, manage memory and knowledge grounding, and operate reliably in production over
extended periods.
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This is a senior individual contributor leadership role. You will define architectural patterns, raise
engineering standards, mentor other engineers, and partner closely with Applied AI, Product
Engineering, and Platform teams to translate cutting-edge research into scalable enterprise
solutions.
Success in this role is measured not by prototypes, but by robust, production-grade agentic
systems shipped to customers.
Required Qualifications
● Bachelor’s or Master’s degree in Computer Science, Software Engineering, or related
field.
● 8–12+ years of professional software engineering experience.
● 3+ years building and deploying production-grade agentic AI systems.
● Deep hands-on experience with:
○ Multi-agent orchestration frameworks (LangGraph, LangChain, LangSmith, or
equivalents)
○ RAG pipelines and memory systems
○ Agent evaluation methodologies
● Strong proficiency in Python and backend cloud services (AWS preferred).
● Proven track record delivering complex AI systems into production.