Staff Product Manager - Applied AI Workflow
Aidashinc · Bengaluru, Karnataka, India; Gurugram, Haryana, India · 2026-06-07
About this role
<div class="content-intro"><p><strong>About AiDASH</strong><br><br><span data-teams="true">AiDASH is leading the PreventionFirst™movement for electric utilities and transforming grid resilience through its pioneering platform that unifies vegetation, asset, storm, and wildfire intelligence. Powered by SatelliteFirst™ Inspection &amp; Monitoring, AiDASH delivers comprehensive visibility across the entire grid at the right frequency and budget, using the right data modality. More than 200 customers trust AiDASH to keep the lights on, spend where it counts, and defend every decision, Securing Tomorrow across every mile of the grid.</span> Learn more at <a href="https://www.aidash.com." target="_blank">www.aidash.com.</a></p> <p><span data-contrast="auto">The&nbsp;PreventionFirst&nbsp;movement is growing, and so is the recognition behind it. In 2026, Forbes named&nbsp;AiDASH&nbsp;one of America's Best Startup Employers for the 4th consecutive year, and TIME included&nbsp;AiDASH&nbsp;among America's Top GreenTech Companies for the 3rd year in a row.&nbsp;</span><a href="https://www2.deloitte.com/us/en/pages/technology-media-and-telecommunications/topics/north-america-technology-fast-500.html?utm_source=bngaiwebsite&amp;utm_medium=referral&amp;utm_campaign=evolve-banner"><span data-contrast="none"><span data-ccp-charstyle="Hyperlink">Deloitte Technology Fast 500</span></span></a><span data-contrast="auto">™ ranked&nbsp;AiDASH&nbsp;No. 12 in the San Francisco Bay Area, and No. 59 overall in their&nbsp;selection&nbsp;of the top 500 for 2024.</span><span data-ccp-props="{&quot;335551550&quot;:0,&quot;335551620&quot;:0}">&nbsp;</span></p> <p><span data-contrast="auto">Join us in Securing Tomorrow Together!</span><span data-ccp-props="{&quot;335551550&quot;:0,&quot;335551620&quot;:0}">&nbsp;</span></p></div><h4>The Role</h4> <p><span data-contrast="auto">Reporting to the VP of Product Management &amp; Process Excellence, you'll own the production workflows that transform raw satellite imagery into customer-grade insights — designing, automating, and continuously improving the pipelines that sit at the heart of how AiDASH delivers value.</span></p> <p class="font-claude-response-body break-words whitespace-normal leading-[1.7]">You'll start by going deep on our Vegetation Management Workflow (IVMS) — where complexity is highest and the automation upside is largest. From there, the scope grows to cover Asset Inspection &amp; Monitoring (AIMS) and Climate Risk Intelligence (CRIS).</p> <p class="font-claude-response-body break-words whitespace-normal leading-[1.7]">You won't be designing customer-facing product features. You won't be building the internal platform (that's our Platform PM, your closest peer). You'll be designing the operating model that connects them — the steps, frameworks, and policies that govern how an insight gets produced, who or what handles each step, and where humans stay in the loop.</p> <h4>How you'll make an impact:</h4> <ul> <li><strong><span data-contrast="auto">Workflow design across products: </span></strong><span data-contrast="auto">Define what the production workflow looks like end-to-end for each product: the sequence of steps, the cohort logic (which customers / geographies / products take which path), the handoffs, and the SLAs</span></li> <li><strong><span data-contrast="auto">Step-level frameworks: </span></strong><span data-contrast="auto">Author the operating frameworks for individual steps — e.g., the image acquisition framework (when do we re-order? from which vendor? what freshness threshold?), the model QC framework (what's the sampling strategy by model age, terrain, sensor?), and similar for every critical step</span></li> <li><strong><span data-contrast="auto">Autonomy and human-in-the-loop policy: </span></strong><span data-contrast="auto">Decide where the workflow runs autonomously and where humans intervene. Set and own the confidence thresholds at which model output is trusted enough to drop QC. The technical specifics — sampling strategies, model evaluation methods, HITL mechanics — are owned by a pod of applied AI data scientists and analysts you'll partner closely with. You own the policy decision; they own the underlying technical work that informs it</span></li> <li><strong><span data-contrast="auto">Cohort logic and CS alignment: </span></strong><span data-contrast="auto">Decide which customers get which workflow flavor. CS and leadership are key stakeholders you'll bring along</span></li> <li><strong><span data-contrast="auto">Requirements to Platform PM: </span></strong><span data-contrast="auto">Translate workflow design into clear system requirements (e.g., "at step X, capture labels with confidence scores and reviewer ID"). Platform PM owns the system spec; you own that the workflow as designed produces the data and outcomes you need</span></li> <li><span data-ccp-props="{&quot;201341983&quot;:0,&quot;335559739&quot;:100,&quot;335559740&quot;:300}"><span class="TextRun…
Skills asked for
- data science
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