A productized engineering service that turns promising AI?-agent prototypes into evaluated, observable, production-ready workflows.
Added Aug 5, 2026
High opportunity (84%)
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AI? product companies can prototype capable agents but struggle to make them dependable in production. Real traffic is noisy, ground truth is incomplete, failures cross model and runtime boundaries, and internal product engineers often lack time to build evaluation infrastructure while also shipping features.
Offer a fixed-scope productionization sprint that maps one critical agent workflow, builds a representative evaluation suite, instruments production traces, diagnoses failure modes, and hardens the agent loop. Deliver the evaluation harness, reliability baseline, prioritized remediation plan, and implementation of the highest-impact fixes, followed by an optional managed evaluation service.
Companies are moving agents into infrastructure and back-office workflows where mistakes have operational consequences. The signals show repeated investment in research engineers who can connect prototypes, production traffic, evaluations, and dependable product features.
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Partner with engineering leads across infrastructure, supply chain, and systems software to identify operational bottlenecks and deploy domain-specific automated agents. Establish platform product metrics for developer velocity, agent reliability, precision, recall, latency, and token cost attribution.
Own the technical architecture behind our workflow agents: orchestration, model serving, latency, cost per task, and failure handling at scale Partner with our Product Manager, AI to define what “reliable enough to submit” means, and build the engineering systems that gate release against that bar
Develop evaluation infrastructure that measures model reliability for enterprise and public sector customers Ship agentic AI applications and the tooling that makes them observable, testable, and safe to deploy
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