The Role

We're looking for a hardware engineer to own the silicon-level foundations of our technology. You'll connect hardware security features to AI workloads, building verifiable computation pipelines where we can statically derive what a GPU kernel should compute and cryptographically prove that it did. You'll work directly with silicon vendors, design attestation systems for modern accelerators, and build the tamper-proof link between a model's architecture and its execution on hardware.

What You'll Do

• Design verifiable compute pipelines that derive hardware behavior expectations from model definitions and tiling configurations, then prove execution integrity
• Build low-level software (C, C++, Rust) that interfaces with TEEs, secure enclaves, and cryptographic accelerators to attest to chip location and computation integrity
• Implement static kernel analysis tools to extract memory access patterns and computational structure from GPU kernels (Triton, CUTLASS, PTX/SASS)
• Serve as technical liaison with silicon vendors (NVIDIA, AMD, Intel) on security architectures, side-channel implications, and next-generation accelerator roadmaps

What You'll Bring

• BS, MS, or PhD in Computer Engineering, CS, or EE with a focus on computer architecture, compilers, or systems security
• Deep understanding of GPU architecture: memory hierarchies, tensor core operations, tiling strategies, and how logical tensors map to physical hardware
• Strong systems programming in C, C++, or Rust with experience interfacing with hardware security primitives
• Experience with CUDA, Triton, or CUTLASS kernel programming

Bonus

• Familiarity with MLIR/LLVM or compiled binary analysis
• Experience with hardware performance counters (Nsight Compute, CUPTI)
• Knowledge of TEEs (Intel SGX/TDX, AMD SEV)
• Interest in formal methods or layout algebra

We are open to hiring both early-career and experienced candidates. For the latter, we are open to higher compensation and more senior titles. We will also consider exceptional candidates on a part-time basis.

The Role

Lucid has a major grant-funded research and deployment program underway with a leading European research institute, focused on building verifiable AI infrastructure. The program spans multiple parallel workstreams (hardware verification, secure compute, and assurance tooling) and needs a dedicated TPM to own execution.

You're a TPM or senior program manager from a hardware, infrastructure, or systems company. You've managed complex multi-stakeholder programs with external partners and are used to imposing structure where there isn't any. You're comfortable with hardware development timelines and constraints, even if you're not designing the hardware yourself.

What You'll Do

• Own end-to-end execution of a multi-workstream, grant-funded program with a European research institute
• Define scope, milestones, dependencies, and risk across hardware verification, secure compute, and assurance tooling workstreams
• Coordinate external partners and internal engineering, keeping parallel workstreams aligned to hardware development timelines
• Own grant compliance and milestone reporting, translating technical complexity into clear updates for leadership and non-technical partners

What You'll Bring

• Strong program management fundamentals: scope, milestones, dependencies, risk, and resource planning
• Experience managing programs with external partners and multiple parallel workstreams
• Enough hardware or IT infrastructure exposure to understand the cadence and constraints of hardware-adjacent projects
• Comfort with ambiguity and the ability to build program structure from scratch

Nice-to-Haves

• 5+ years of TPM experience (strong candidates with less will be considered)
• Background in hardware security, trusted computing, or data center infrastructure
• Familiarity with grant compliance and milestone reporting
• Experience at hardware, defense/aerospace, infrastructure, or research-adjacent organizations

Early-stage equity in a company working on a problem with real geopolitical stakes, founding-team-level influence on product and strategy, a small team with low bureaucracy, and work on infrastructure that makes AI safer and more accountable rather than only faster.

The Role

Lucid's founding team is strong on cryptography, hardware security, and policy, but we're looking for someone who has operated inside the AI cloud infrastructure world. This hire brings industry credibility, a real rolodex, and the strategic instincts to shape Lucid's commercial go-to-market in AI compute. This is a business-shaping role with founding-team-level influence.

You're a senior commercial leader from a neo-cloud or AI infrastructure company. You've been in the rooms where GPU supply, colo contracts, and enterprise cloud deals get done, and you know the buyers, operators, and supply chain personally.

What You'll Do

• Own Lucid's commercial go-to-market in AI compute and land the first wave of enterprise contracts before we have brand pull
• Structure multi-year capacity commitments with takedown schedules and capex-heavy contract terms
• Advise the founding team on positioning and strategy, and recruit and build the commercial function
• Carry a number: personally close eight-figure-plus deals end-to-end with Fortune 500 buyers

What You'll Bring

• Early neocloud experience: joined a GPU cloud at seed or Series A and personally landed the first wave of enterprise contracts
• Operating leadership: the strategic breadth, recruiting ability, and ambition to own and grow Lucid's commercial function as the company scales, ideally signaled by prior founder/CEO experience or GM/P&L ownership
• Enterprise sales: personally carried a number and closed individual eight-figure-plus deals end-to-end with Fortune 500 buyers
• Capex / infra fluency: personally structured multi-year capacity commitments and capex-heavy contract terms (wholesale datacenter sales, energy PPAs, or operating roles at a neocloud)

Nice-to-Haves

• Experience with sovereign cloud, data residency, or regulated verticals (finance, healthcare, defense)
• Familiarity with confidential computing, TEEs, or hardware security
• Experience at a company at a similar stage (sub-50 people, pre-Series A or Series A)
• Genuine interest in AI safety, governance, or responsible deployment

Early-stage equity in a company working on a problem with real geopolitical stakes, founding-team-level influence on product, positioning, and strategy, a small team with low bureaucracy, and work on infrastructure that makes AI safer and more accountable rather than only faster.