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Review and challenge model evaluation results, including assessments of performance (e.g. groundedness, factual accuracy, retrieval quality, relevance, and instruction adherence), and evaluate the reliability of LLM-as-a-Judge methodologies through calibration against human-labelled benchmarks.
Solution and proposal development: Translate requirements into solution concepts, PoC scope, work plans, assumptions, risks and proposal content; coordinate inputs from architects, engineers, data specialists and partners.
Collaborate closely with business stakeholders, data scientists, engineers, and IT teams to translate business requirements into technical AI solutions.
You will own production reliability through observability, service-level targets, incident improvement and mandatory participation in on-call rotations.
Reporting directly to the AI Architect, the Staff AI Systems Engineer will serve as a key technical partner in translating AI product requirements and architectural vision into deployable AI solutions.
Assist in developing AI solution architectures, HLD/LLD, data-flow designs, sizing, BoM, costing, implementation roadmaps and proposals for RFI/RFP/tenders.