Build verifiable AI for the
highest-stakes systems.
Zal Logic is assembling an elite engineering and research roster to solve the hardest open problem in artificial intelligence: eliminating statistical hallucination and establishing verifiable mathematical truth across global media, defense intelligence, and judicial evidence.
Mathematical Invariants
We do not build toy demos. Our systems run automated theorem proving (Z3 SMT) and causal Pearlian surgeries on exascale compute clusters.
Protecting Global Reality
Our code protects federal judiciaries, sovereign defense ministries, and global newsrooms against synthetic media warfare and algorithmic manipulation.
Line-by-Line Craftsmanship
Flat hierarchy led by scientists and systems architects. Complete autonomy, frontier computational budgets, and relentless technical standards.
Active Engineering & Research Disciplines
Foundational Research Scientist • Neurosymbolic Logic & SMT
Design continuous-to-discrete bridge layers between latent perception manifolds and first-order SMT-LIB v2 invariant constraints. Formulate loss functions that penalize physical invariant contradictions and guide MCTS hypothesis tree search.
Staff Distributed Systems Engineer • Sovereign Infrastructure
Architect high-throughput forensic ingestion pipelines processing gigabytes of raw multi-spectral media per second. Optimize air-gapped sovereign Kubernetes clusters, custom CUDA/C++ kernels, and Zero-Trust Merkle state storage.
Lead Cryptographic Provenance & Attestation Architect
Design client-side zero-knowledge attestation engines, C2PA manifest validators, and judicial Merkle leaf-to-root proof generators that satisfy Federal Rules of Evidence 902(14) in international court jurisdictions.
Principal Solutions Architect • Sovereign & Defense Deployments
Work directly with sovereign defense ministries, federal judiciaries, and tier-1 banking institutions to design and deploy private air-gapped sovereign clusters and integrated verification workflows.
Apply Directly to Our Talent Team
Send your CV, GitHub handle, or links to published research papers directly to our Human Resources channel at [email protected]. We review all engineering and research submissions directly.