AI Agentic Workflow Reviewer at Innodata Inc.

<div class="content-intro"><p>Innodata&nbsp;(Nasdaq: INOD) is a global data engineering company. We believe that data and Artificial Intelligence (AI) are inextricably linked.&nbsp;Our mission is to enable the responsible advancement of artificial intelligence by providing the data, evaluation frameworks, and human expertise required to build AI systems that can be trusted at scale.&nbsp;We provide a range of transferable solutions, platforms, and services for Generative AI / AI builders and adopters. In every relationship, we honor our 36+ year legacy delivering the highest quality data and outstanding outcomes for our customers.</p></div><p class="Paragraph SCXW66493682 BCX2"><strong>Scope of the Role:&nbsp;</strong></p> <p>We're building a dedicated reviewer team to evaluate complex, real-world agentic AI workflows, assessing whether AI agents complete tasks safely, respect user intent and consent, and hold up under close scrutiny. This isn't routine content moderation: reviewers work through ambiguous, multi-step scenarios where judgment calls matter as much as checklists. You'll operate inside isolated test environments, apply structured rubrics, and help calibrate what "safe and policy adherent agent behavior" actually looks like.</p> <p class="Paragraph SCXW66493682 BCX2"><strong>What You’ll Own:</strong></p> <ul> <li><span data-contrast="auto">Review multi-step agent task trajectories against rubric-based criteria covering task success, safety, and policy adherence</span></li> <li><span data-contrast="auto">Evaluate whether an agent respected user agency and informed consent — not just whether it followed literal instructions</span></li> <li><span data-contrast="auto">Apply privacy guardrails when reviewing tasks involving sensitive or personal data</span></li> <li><span data-contrast="auto">Work inside isolated test environments, including verifying environment resets between test runs to prevent cross-contamination</span></li> <li><span data-contrast="auto">Flag and escalate safety-relevant or ambiguous findings through defined escalation paths</span></li> </ul> <p><strong>You’ll Thrive in This Role If You Have:</strong></p> <ul> <li><span data-contrast="auto">Bachelor's degree or equivalent practical experience</span></li> <li><span data-contrast="auto">2–5+ years in quality review, QA/QC, trust &amp; safety, content moderation, data annotation, or a similarly judgment-intensive review role</span></li> <li><span data-contrast="auto">Strong written communication – you can justify a scoring decision clearly enough for someone else to audit it</span></li> <li><span data-contrast="auto">Comfort with ambiguity and structured decision-making under a rubric, rather than needing a fixed rulebook for every case<br></span></li> <li><span data-contrast="auto">Baseline understanding of AI/ML concepts and how AI agents complete tasks (can be learned through onboarding, but some familiarity helps)</span></li> </ul> <p><em>The expected hourly salary range for this position is $50-$55p/hour, based on experience, skills, and qualifications.</em></p> <p>&nbsp;</p><div class="content-conclusion"><p></p> <p class="x_elementToProof"><em>Please be aware of recruitment scams involving individuals or organizations falsely claiming to represent employers. Innodata will never ask for payment, banking details, or sensitive personal information during the application process. To learn more on how to recognize job scams, please visit the Federal Trade Commission’s guide at&nbsp;</em><a href="https://consumer.ftc.gov/articles/job-scams." target="_blank">https://consumer.ftc.gov/articles/job-scams.</a><em>&nbsp;</em></p> <p class="x_elementToProof"><em>If you believe you’ve been targeted by a recruitment scam, please report it to Innodata at&nbsp;</em><a href="mailto:[email protected]" target="_blank">[email protected]</a><em>&nbsp;and consider reporting it to the FTC at&nbsp;</em><a href="http://reportfraud.ftc.gov/" target="_blank">ReportFraud.ftc.gov</a><em>.</em></p> <p></p></div>