Agentic Studio Labs is led by Jonathan Major, a senior AI engineer with deep enterprise platform, security, and regulated-systems experience. He gets brought in when the work needs to ship cleanly, survive real constraints, and hand off without drama.
Jonathan works best on serious builds: AI products, internal systems, and agentic workflows where architecture, trust boundaries, and production handoff matter. The work is less about abstract AI strategy and more about getting a real system built, deployed, and handed over cleanly.
The value here is not generic AI enthusiasm. It is the combination of delivery experience, enterprise operating history, and security judgment that makes serious systems easier to trust.
Agentic Studio Labs sits at the intersection of AI engineering, enterprise platform delivery, and security-sensitive operating environments.
Builds and deploys AI systems that do real work: agentic workflows, retrieval systems, evaluation layers, context infrastructure, and productized internal tooling.
Strong on orchestration, tool use, MCP servers, LangGraph-style multi-agent patterns, and the hard edges around handoff, control, and observability.
Deep experience with trust boundaries, AI risk, compliance programs, audit workflows, threat modeling, MDR/DFIR, and production controls for regulated work.
Comfortable in environments where deployment quality, integration complexity, and executive credibility matter as much as model choice or demo quality.
The detailed profile lives on the full `whoami` page. This is the buyer's-eye summary.
Builds production AI systems for teams with real workflows, meaningful constraints, and a need for clean technical handoff.
Led security and compliance work across SOC 2, ISO 27001, privacy, threat modeling, DFIR, and operational audit readiness while also building applied AI systems and supporting infrastructure.
From founding engineering leadership through enterprise platform execution, including engineering, operations, InfoSec, and delivery responsibility in complex data environments.
Built large-scale delivery, testing, and operational systems in high-stakes financial and enterprise software environments.
If you are trying to assess fit, the next best move is either to review representative work or look at the full technical profile and resume. When there is a real system on the table, book the scoping call.