Supercharge your analytics and improve marketing outcomes with Newton, your team of marketing analytics agents. Backed by Bessemer.
About the role
We run everything through an AI-first lens, because it is the only way quality scales. If a quality task is repeatable, an agent does it and you supervise; if it takes judgment, that is where you spend your time. Found on 1752vc Careers, the job board for startup and VC roles.
What they're looking for
- Measure the AI: agent output varies run to run, so “correct” is a range you define with evals, rubrics and scoring, not an exact-match assertion
- Let agents run the checks: agents run suites, triage failures and draft repro-ready defects, you design their roles and guardrails and review what they produce
- Make Newton verifiable by agents: you keep the product and pipeline observable and fixture-friendly so agents can verify it without a human in the loop
- Handle non-determinism with rigor: repeated runs, pass-rate thresholds and simple statistics, so a flaky agent is a measured finding, not an anecdote
- Turn production and customer signal into evals: mine logs, error tracking and customer reports so every escaped bad-behavior case becomes a permanent eval, ideally drafted by an agent and reviewed by you
- Probe AI-specific risk: prompt injection, data leakage across users, projects and permissions, hallucinated or ungrounded numbers in analytics output, cost and latency regressions
More about this role
QA Engineer, AI-Native Quality
Newton Research · Research & Development · Boston / Needham, MA
Company Description
Newton Research is a fast-growing software start-up founded by repeat entrepreneurs and well-funded by blue chip venture capital firms. We are building the next generation of the closed loop media lifecycle, developing AI agents that leverage the latest in LLMs and generative AI with specialized knowledge. Our products generate actionable business insights for our customers and partners, assisting in each step of the media planning, buying and measurement lifecycle.
About the Role
Newton ships on a sprint cadence through a develop, stage and customer-environment pipeline, and the product surface is wide: conversations, blueprints, connectors, scheduled tasks, permissions and sharing, SSO, and AI agents whose behavior is not fully deterministic. A missed regression lands in front of a media planner or a customer's security review.
We run everything through an AI-first lens, because it is the only way quality scales. If a quality task is repeatable, an agent does it and you supervise; if it takes judgment, that is where you spend your time.
The gap this hire fills:...
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