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Dipp AI Technologies is seeking a senior role to design the telemetry architecture for long-running, multi-agent workflows across models, tools, data boundaries and enterprise systems.
The role focuses on preserving causality, distinguishing proposed actions from committed ones, and enabling redaction and access control for sensitive telemetry. You will work across the Immutable Audit Ledger and data governance layers, collaborating with a New York-based founding team.
Build the evidence layer that lets operators reconstruct every agent decision across models, tools, data boundaries and enterprise systems.
Observability in Orcher is not a dashboard added after execution. It is the operating record that connects a human directive to the identity used, policies evaluated, model and compute route selected, tools called, cost incurred and outcome committed.
You will design the telemetry architecture for long-running, multi-agent workflows that cross frontier APIs, open-weight models, private infrastructure and enterprise systems of record. The hard problems include preserving causality across asynchronous boundaries, distinguishing a proposed action from a committed one, keeping high-cardinality evidence queryable, and making partial failure legible without weakening customer data controls.
This role works across the Immutable Audit Ledger, Cost Governance and Data Control Gateway. Your work will help a security leader investigate an anomalous action, a finance owner explain model spend, and an operator determine whether a workflow completed under the authority and limits originally assigned to it.