Hiring: Senior Staff Engineer, System Architect (R5843) Company: Shield AI Location: San Diego, CA Job Posted Time: 2026-09-10 10:33:14 Employment Type: Full-time / Hybrid Target Skills & Keywords : AI, Infrastructure as Code, Kubernetes, MLOps, S3, Segment About the job Experience: •10+ years of experience in software or software-intensive systems development, design, and/or architecture. Required Skills: •This ecosystem combines developer tools, APIs, data infrastructure, simulation, AI/ML workflows, and GenAI-enabled automation to accelerate the delivery of autonomous capabilities using Vision-Language Models (VLMs), Vision-Language-Action (VLA) models, world models, foundation models, and other applied AI technologies. •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. Qualifications: •Demonstrated experience architecting complex software platforms, developer ecosystems, SDKs, APIs, AI/ML platforms, or distributed systems. •Understanding of how data, training configurations, model artifacts, evaluations, software, and deployments must be connected to provide end-to-end traceability, reproducibility, and auditability. •Practical understanding of technologies such as 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. •Direct experience developing, training, tuning, evaluating, applying, or deploying VLMs, VLAs, world models, foundation models, or related modern AI models. Compensation: •$170,000 - $310,000 / year •Pay within range listed + Bonus + Benefits + Equity Interested candidates, please apply directly through the job posting on company's career page or try via AI auto apply on this platform. Don't miss this opportunity to join a forward-thinking team!