Embark on a transformative journey with Cognite a global SaaS forerunner in leveraging AI and data to unravel complex business challenges through our cutting-edge offerings including Cognite Atlas AI an industrial agent workbench and the Cognite Data Fusion (CDF) platform. We were awarded the 2022 Technology Innovation Leader for Global Digital Industrial Platforms & Cognite was recognized as 2024 Microsoft Energy and Resources Partner of the the realm of industrial digital transformation we stand at the forefront reshaping the future of Oil & Gas Chemicals Pharma and other Manufacturing and Energy sectors. Join us in this venture where AI and data meet ingenuity and together we forge the path to a smarter more connected industrial future.
Impact: Cogniters strive to make an impact in all that they do. We are result-oriented always asking ourselves.
Ownership: Cogniters embrace a culture of ownership. We go beyond our comfort zones to contribute to the greater good fostering inclusivity and sharing responsibilities for challenges and success.
Relentless: Cogniters are relentless in their pursuit of innovation. We are determined and deliverable (never ruthless or reckless) facing challenges head-on and viewing setbacks as opportunities for growth.
As a Principal Product Manager youll be responsible for defining and delivering the next generation of our contextualization tools. This isnt about traditional data integration; its about harnessing the power of AI to transform how industrial data particularly engineering diagrams and unstructured documents is understood and connected. Youll lead the charge in shifting from deterministic rule-based systems to intelligent self-correcting and probabilistic AI-driven solutions that drastically reduce manual effort and improve data quality for our customers .You ill act as the key link between our engineering team in Bengaluru our internal global stakeholders and our global customer base. Youll work closely with customers to understand their challenges define product requirements and guide the team in building scalable user-centric solutions. This role requires a blend of deep technical expertise in machine learning and a strong product management mindset focused on user outcomes and market needs.
Key Responsibilities
Define Product Strategy: Develop and own the product vision and strategy for AI-driven contextualization aligning it with Cognites overall mission and market opportunities.
Lead with Empathy: Engage with customers and internal stakeholders to deeply understand their problems pain points and workflows related to digitizing and connecting data.
Translate Vision to Execution: Author detailed product requirements and user stories for the engineering team ensuring a clear and shared understanding of goals. Youll be instrumental in prioritizing the product backlog to maximize impact.
Navigate the AI Landscape: Drive the adoption of advanced machine learning techniques including computer vision models (e.g. Faster R-CNN YOLO Siamese Networks) and other AI/ML approaches for symbol text and line detection in engineering diagrams.
Champion a Shift in Mindset: Lead the transition from manual deterministic methods to intelligent probabilistic and agentic workflows that can self-correct and optimize based on user-defined expectations rather than rigid manual configurations.
Manage Cross-functional Collaboration: Work closely with engineering UX/UI data science and customer-facing teams to deliver a cohesive product experience. Youll also need to navigate the complexities of a multi-cloud environment considering platform services from AWS Azure and GCP.
Build the Team: Play a key role in hiring and mentoring product managers and other talent as the team grows in Bengaluru.
Required Skills & Experience
Priority 1: AI-Driven Product Development & Market Launch: Proven experience in a product leadership role for AI/ML-driven products. You must have a demonstrated track record of launching successful AI products to market at scale. You should have a solid understanding of machine learning concepts including model training data sets feature extraction and different model architectures like convolutional neural networks.
Priority 2: Industrial Data Expertise: Experience in the industrial sector is highly desirable. You should have a strong understanding of industrial data domains including engineering data sensor data and data from ERP and MES systems. Familiarity with relevant industry standards is a significant advantage including but not limited to:
Engineering and Asset Data: DEXPI CFIHOS ISO 14224 ISO 15926
Enterprise and Business Data: ISA-95 B2MML
Product and Classification Data: ECLASS UNSPSC GPC
Data-Centric AI Leadership: You have a proven track record of managing and leading teams that prioritize data quality and are structured for success with probabilistic models. This includes experience with:
Data Collection & Labeling: Successfully managing the collection curation and labeling of huge volumes of complex data.
Data - First Methodology: Implementing a test-driven AI/ML methodology using evaluation and benchmark datasets to drive continuous model improvement and measure performance.
AI - Driven Configuration: A strong understanding of how to use AI to optimize product configurations based on user-described success metrics moving beyond manual parameter tuning.
Hands-on Experience with AI Projects: Direct experience leading projects involving computer vision and object detection ideally on complex industrial imagery or technical diagrams. Knowledge of techniques for synthetic data generation and fine-tuning models on limited proprietary data is a significant advantage.
Product Management Acumen: A minimum of 8 years of product management experience with a track record of successfully bringing complex technical products to market.
Cloud Computing and Multi-cloud Solutions: Experience with cloud platforms such as AWS Azure and/or Google Cloud. A strong understanding of how to build and manage products that can be deployed across different cloud providers is essential. Relevant services include:
AWS: SageMaker Lambda Bedrock Data Automation Textract
Azure: Azure Machine Learning Azure Functions Azure AI Document Intelligence
GCP: Google Cloud Vertex AI Google Cloud Functions Google Cloud Document AI
Technical Communication: The ability to communicate complex technical concepts to both technical and non-technical audiences translating AI capabilities into tangible business value.
Strategic Thinking: The ability to think beyond current solutions and envision a future where AI radically simplifies industrial data management. You should be able to define what good is and establish metrics to measure success.
Join the global Cognite community!
- Join an organization of 70 different nationalities with Diversity Equality and Inclusion (DEI) in focus
If youre excited about the opportunity to work at Cognite and make a difference in the tech industry we encourage you to apply today! We welcome candidates of all backgrounds and identities to join our team.
We encourage you to follow us on Cognite LinkedIn; we post all our openings there.
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