Senior Staff Engineer (System Architect)

Join Shield AI as a Senior Staff Engineer (System Architect) and take ownership of the architecture of Hivemind Forge, an AI development ecosystem. You will work at the intersection of software architecture, AI/ML, data architecture, systems engineering, developer experience, and Generative AI-enabled engineering. Your responsibilities will include defining and maintaining architecture products, establishing architectural patterns, and ensuring the ecosystem can operate across various deployment environments. You will also guide architecture for workflows spanning data ingestion and curation, model training and tuning, evaluation, optimization, validation, and deployment.

• Own and evolve the architecture of the Hivemind Forge AI development ecosystem, ensuring architectural integrity across development teams.
• 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.

• 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
• Strong technical leadership and communication skills, with the ability to guide detailed design and maintain alignment across multiple engineering teams
• 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 technologies such as Kubernetes, Slurm or comparable workload schedulers, containerization, infrastructure as code, and object/data storage platforms such as S3-compatible systems
• Demonstrated experience architecting complex software platforms, developer ecosystems, SDKs, APIs, AI/ML platforms, or distributed systems
• 10+ years of experience in software or software-intensive systems development, design, and/or architecture
• Experience designing AI-native or agentic workflows, including tool use, orchestration, retrieval, structured outputs, evaluation, and human-in-the-loop controls
• Experience with MLOps, distributed training, simulation, synthetic data generation, experiment tracking, or model registries
• Direct experience developing, training, tuning, evaluating, applying, or deploying VLMs, VLAs, world models, foundation models, or related modern AI models
• Experience designing, deploying, or operating software and AI/ML platforms in classified, air-gapped, disconnected, or restricted-network environments
• Experience with hybrid-cloud, multi-cloud, on-premises, or edge deployment architectures
• Experience architecting autonomy, robotics, aerospace, unmanned systems, or other Physical AI applications
• Experience applying MBSE methods and tools, including SysML and Cameo/MagicDraw
• Experience delivering defense, aerospace, safety-relevant, or other high-assurance systems requiring rigorous configuration management, verification, and traceability