IT & Infrastructure Architect (EDA / SoC / AI Platforms)

About TylSemi, Inc. The Opportunity The AI infrastructure market is exploding. Every hyperscaler, every cloud provider, every AI company is building custom silicon. But they all face the same problem: how do you connect hundreds of chips, deliver clean power at scale, and move terabits of data without melting the package? That's what we solve. TylSemi builds the chiplet infrastructure IP — the IO, power delivery, and interconnect building blocks — that makes AI/HPC systems actually work at scale. This isn't a nice-to-have. It's the critical path. Why Now The Market Window The semiconductor industry is going through its biggest architectural shift in 40 years: • Moore's Law is dead. 2nm and beyond delivers marginal performance gains. The future is chiplets, not monolithic dies. • Custom silicon is now mainstream. Google, Microsoft, Amazon, Meta, OpenAI — they're all designing their own ASICs. The $50B custom silicon market is growing 30% annually. • IO and power are the bottleneck. Solve hard problems and provide something which is a category in itself. Translation: We're entering the market at exactly the moment when every major AI/HPC player needs what we're building, and their alternatives are disappearing. Culture & Team: How We Work No Politics, No Bureaucracy There are no layers, no approval chains, no corporate theater. • If you have an idea, we test it. If it works, we ship it. • No endless meetings, no PowerPoint presentations to convince middle management. Remote-Friendly, Global Team • US team: Bay Area preferred, but we hire the best people regardless of location • India team: Building a world-class design center in Bangalore Move Fast, Ship Real Products We're not a research project. We have paying customers, committed capital, and aggressive timelines. This is a company, not a lifestyle business. We're building to win. What We Value • Ownership mindset. You're not here to execute someone else's roadmap. You're here to define it. • Bias for action. We move fast. Analysis paralysis doesn't fly here. • Deep technical expertise. This is hard engineering. We need people who've shipped real silicon and debugged real hardware. • Low ego, high standards. We don't care about titles or politics. We care about results. The Ask If you're reading this, you're probably comfortable. You have a good job at a stable company with all the benefits. We're asking you to walk away from that and bet on us. Here's why you should: • The market is real. AI infrastructure spending is $200B+ annually and growing 40% YoY. Every hyperscaler needs what we're building. • The team has done this before. We've built and exited semiconductor companies at scale. This isn't our first rodeo. • The traction is de-risked. We have LOIs, strategic investors, and a clear path to revenue. • The work is consequential. You're not optimizing someone's ad click-through rate. You're building the silicon infrastructure that powers AI. This is the bet. Join us and build something that matters. Or stay comfortable. No judgment. But if you're the kind of person who wants to take the shot, we'd love to talk. READY TO JOIN? Role Overview We are looking for a hands-on and highly strategic IT & Infrastructure Admin to build and manage the end-to-end compute, storage, network, and EDA infrastructure required for designing complex SoCs across digital and analog domains . This role goes beyond traditional IT—it requires deep ownership of EDA environments, compute strategy (cloud vs on-prem), cost optimization, and AI infrastructure enablement , ensuring high performance, scalability, and reliability for engineering teams. Key Responsibilities EDA & Engineering Infrastructure Own setup, deployment, and management of EDA tools and environments for: Digital design and verification Analog and custom design flows Manage tool installations, upgrades, and compatibility across flows Drive EDA license management , including: Forecasting demand across teams and projects Optimizing utilization and cost Vendor coordination and negotiations Ensure high availability and performance of compute farms and storage systems Compute & Platform Strategy Define and execute strategy for cloud vs on-prem infrastructure : Evaluate AWS (or other cloud platforms) vs owned/rented servers Build cost models and ROI analysis for different scaling scenarios Design scalable infrastructure for: Large regressions (DV workloads) RTL synthesis and physical design Analog simulations (compute-intensive workloads) Optimize job scheduling, workload distribution, and resource utilization Network & Systems Management Design and manage high-performance network infrastructure : Low-latency, high-throughput connectivity for EDA workloads Secure remote access for distributed teams Manage: Servers, storage (NAS/SAN), and backup systems OS environments (primarily Linux-based) Data security, access control, and disaster recovery AI Infrastructure & Enablement Support deployment and scaling of AI/ML infrastructure for engineering workflows Work with AI and engineering teams to: Enable AI agent workflows Optimize compute usage (GPU/CPU allocation) Define and enforce AI usage guardrails , including: Data security and IP protection Safe usage policies for internal and external AI tools Manage token usage, cost tracking, and access control for AI platforms Planning, Forecasting & Cost Optimization Develop and maintain forecasts for: Compute infrastructure (cloud + on-prem) EDA licenses Storage and network capacity Continuously optimize for cost vs performance vs scalability trade-offs Provide leadership with data-driven recommendations on infrastructure investments Required Qualifications Bachelor’s degree in Computer Science, Electrical Engineering, or related field 10+ years of experience in IT infrastructure / systems engineering , preferably in semiconductor or EDA environments Strong experience with: EDA tool environments (Synopsys, Cadence, Siemens/Mentor) Linux system administration Compute cluster management and job schedulers (LSF, Slurm, etc.) Experience managing large-scale compute and storage systems Strong understanding of networking fundamentals (high-performance networks preferred) Experience with cloud platforms (AWS preferred) Preferred Qualifications Experience supporting SoC design teams (RTL, DV, Analog) Familiarity with analog simulation environments and their compute demands Experience with hybrid cloud architectures Exposure to GPU infrastructure and AI/ML workloads Scripting skills (Python, Bash, etc.) for automation Experience with security and compliance in IP-sensitive environments Key Attributes Strong ownership and end-to-end accountability mindset Ability to balance technical depth with strategic decision-making Bias toward automation, scalability, and efficiency Strong problem-solving and operational excellence Comfortable working in a fast-paced startup environment Success Metrics Reliable, scalable infrastructure supporting high engineering productivity Optimized EDA license utilization and cost efficiency Effective cloud vs on-prem strategy with measurable ROI Minimal downtime and high system availability Secure and efficient AI infrastructure adoption Ability to scale infrastructure seamlessly with company growth