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Senior Staff Engineer, System Architect (R5843)

Shield AI· Hivemind Enterprise Division – Systems
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Hybrid (San Diego, CA), Hybrid (San Mateo, CA)$170k - $310kFull Time EmployeePosted 1mo ago

About the role

Senior-level System Architect responsible for the architecture of Hivemind Forge, an AI development ecosystem enabling developers to build, train, tune, evaluate, optimize, and deploy learning-based autonomy solutions within the Hivemind Enterprise organization.

Responsibilities

  • Own and evolve the architecture of the Hivemind Forge AI development ecosystem.
  • Define and maintain architecture products in an integrated model-based systems engineering (MBSE) environment, connecting architectural intent to engineering execution.
  • Establish architectural patterns, interfaces, APIs, SDK concepts, and technical standards across software, AI/ML, data, simulation, and deployment capabilities.
  • Define the data and metadata architecture underpinning the AI development lifecycle, including schemas, relationships, lineage, provenance, versioning, and lifecycle management.
  • Ensure traceable pedigree across datasets, training configurations, model artifacts, evaluations, software versions, and deployed capabilities to support reproducibility and auditability.
  • Architect GenAI-enabled and agentic development workflows that accelerate data curation, autonomy development, experimentation, evaluation, troubleshooting, and deployment while preserving human oversight, security, verification, and traceability.
  • Define architectural patterns for integrating AI coding assistants, agents, foundation models, and natural-language interfaces with Hivemind development tools, APIs, SDKs, data, simulation, and engineering workflows.
  • Define architecture for scalable AI/ML workloads across cloud, HPC, and on-premises infrastructure, including orchestration, workload scheduling, containerization, storage, and data movement.
  • Ensure the ecosystem can be deployed and operated in classified, air-gapped, disconnected, and other constrained enterprise environments while preserving security, configuration control, and reproducibility.
  • Ensure AI-assisted and agentic development workflows preserve appropriate provenance, traceability, human oversight, verification, security, and reproducibility, particularly when contributing to deployed autonomous capabilities.
  • Guide architecture for workflows spanning data ingestion and curation, synthetic data generation, model training and tuning, evaluation, optimization, validation, and deployment.
  • Review and approve detailed software and data designs, resolve cross-team architectural issues, and maintain architectural integrity through implementation and integration.
  • Partner with software, AI/ML, data, systems, product, and technical leadership teams to reduce the time from mission need to validated, deployable autonomy.

Qualifications

  • 10+ years of experience in software or software-intensive systems development, design, and/or architecture.
  • Demonstrated experience architecting complex software platforms, developer ecosystems, SDKs, APIs, AI/ML platforms, or distributed systems.
  • Experience developing AI/ML solutions using synthetic and real-world data.
  • Experience in data modeling and data architecture, including metadata, lineage, provenance, versioning, and lifecycle management.
  • Understanding of how data, training configurations, model artifacts, evaluations, software, and deployments must be connected to provide end-to-end traceability, reproducibility, and auditability.
  • Experience applying Generative AI, AI assistants, or agents to software, AI/ML, or engineering development workflows.
  • Practical understanding of Kubernetes, Slurm or comparable workload schedulers, containerization, infrastructure as code, and object/data storage platforms such as S3-compatible systems.
  • Strong technical leadership and communication skills, with the ability to guide detailed design and maintain alignment across multiple engineering teams.

Skills

Required:Architecture leadershipMBSE (Model-Based Systems Engineering)

Benefits

  • Pay within range listed + Bonus + Benefits + Equity
  • Temporary employee offer package (applicable after 60 days of employment) with temporary benefits
  • Salary compensation influenced by factors including skill set, experience, licenses/certifications, and location
  • Background check and potential reference check requirements
  • Equal opportunity employment with accommodations available upon request
Last updated Oct 23, 2026. Interested? Apply on the company site.

About Shield AI

Autonomy for the world.

Our mission is to protect service members and civilians with intelligent systems.

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