Principal Product Manager, AiDash
Platform
$200-250k
Office located in Palo Alto, CA
Satellite-first AI applications
Be an early applicant
Satellite-first AI applications
201-500 employees
Be an early applicant
$200-250k
Office located in Palo Alto, CA
201-500 employees
Company mission
To create a greener, cleaner, safer planet from space.
Role
Who you are
- 10–12+ years of experience in product management or technical roles, with a focus on building scalable internal or developer platforms
- 6+ years leading platform product teams in high-growth, fast-paced environments
- Demonstrated experience shipping platform products for enterprise SAAS
- Strong technical foundation — you can go deep with engineering and data science partners, understand architectural trade-offs, and make well-informed decisions
- Excellent analytical and quantitative skills, with a structured, data-driven approach to prioritization
- Outstanding communication and stakeholder management skills — able to influence without authority across engineering, business, and executive audiences
- Experience leading distributed, cross-geography teams
- Bachelor's degree in Computer Science, Engineering, Mathematics, or a related field; MBA is a plus
What the job involves
- As Principal Product Manager – Platform at AiDASH, you will combine the latest machine learning and data science techniques with sharp product and design thinking to build a robust platform that powers AiDASH's growing suite of products
- You will be responsible for building the core of our data management platform, delivery orchestration systems, enabling autonomous decision-making with Hilo, and developing the API layers that allow internal and external systems to interact with out Platform
- Reporting directly to the VP - Product & Engineering, you will shape platform product strategy by connecting the company's vision and goals with a deep understanding of our customers, products, and current and future AI/ML capabilities
- You will own the platform roadmap end-to-end, from ideation through scaling, and partner closely with engineering, data science, and design teams to define the processes that drive high-quality delivery and meaningful business outcomes, while making thoughtful short- and long-term trade-offs
- Define and own the platform product strategy, roadmap, and product definition across the full lifecycle — from concept to scale
- Define and execute the strategy for data ingestion, processing, storage, and governance to support our Spatial and Temporal Single source of Truth
- Partner with data platform engineering, analytics, and business teams to establish a unified data foundation enabling self-serve access and trusted insights
- Drive initiatives around data quality, lineage, versioning, cataloging and observability to ensure data reliability at scale
- Define and track KPIs for platform adoption
- Champion data democratization — enabling both technical and non-technical stakeholders to leverage data effectively
- Own the product vision and roadmap for Agentic AI capabilities within the delivery and operational orchestration domain
- Translate complex delivery workflows into intelligent, autonomous agent pipelines — spanning planning, execution, exception handling, and feedback loops
- Define evaluation frameworks for agent performance, reliability, safety, and human-in-the-loop escalation paths
- Define the strategy for external API layers — covering design standards, versioning, access control, rate limiting, and developer experience
- Own the API product lifecycle from design to deprecation, ensuring APIs are reliable, well-documented, and easy to integrate
- Build and maintain a developer portal and self-service onboarding experience for API consumers
Our take
The growing constellations of satellites delivering high definition earth imaging, along with advancements in AI, have spawned a flourishing business in ‘digital twins’ for global asset management. These digital data-compilation copies of on-the-ground locations can be used to help predict and mitigate the effects of climate disaster events - which cost the US billions of dollars each year.
AiDash’s various products help manage disaster, disruption and wildfires, as well as monitoring vegetation. The latter service, its original one, has a host of high-profile global clients, such as National Grid. The company's expansion into climate resilience demonstrates a keen awareness of both its tech's potential and the direction of the market - with environmental issues becoming even more of a hot topic in recent years.
The company has done well to prove its agility, which may well enable it to stay ahead of more specified rivals as they enter the scene. This includes companies like Kettle and Technosylva which operate in the predictive climate analytics space. AiDash's comparatively diverse offering should help it retain a competitive edge, while the substantial funding it has secured supports the pursuit of heightened global expansion.
Freddie
Company Specialist at Welcome to the Jungle
Insights
Company
Funding (last 2 of 4 rounds)
Apr 2024
$58.5m
SERIES C
Nov 2022
$10m
LATE VC
Total funding: $101.5m
Company benefits
- Multiply your growth - Grow into your best self while you are helping us grow. Where are you on your career path? How can we help?
- Know your view is valued - Your concepts, your perspectives, your opinions, your creativity
- Balance work with life - You’ll need personal time for the things that matter. You’ll have it
- Get world-class rewards - Comprehensive benefits, ESOPs and other perks
Company HQ
University South, Palo Alto, CA
Leadership
Abhishek Vinod Singh
(CEO & Co-founder)Co-founded Mitrr and DbyDX Software, then moved into a SVP and COO role at Kellton Tech Solutions. Most recently spent a decade as co-founder, director, and advisor at Edureka.
Rahul Saxena
(Chief Product & Technology Officer, Co-founder)Spent time in senior Engineering roles at Qwest Software Services and RSA Security, then went on to co-found allMemoirs and Quiklo.
Nitin Das
(Chief AI Officer & Co-founder)Previously directed Applied Research at Kvantum, then acted as Lead AI Scientist for Target. Additionally co-founded Uvaca Private Ltd.
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