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Technical Data and AI Product Manager

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Description

About the Role

We’re looking for a Technical Data & AI Product Manager to join our growing team at Canibuild. This role is ideal for someone who can connect business needs, data opportunities, and emerging AI capabilities to deliver scalable, high-impact solutions.

You’ll work at the intersection of data engineering, AI/GenAI, and product strategy, defining what we should build, why it matters, and how it integrates into our platform. You’ll collaborate closely with engineers, data specialists, and other Product Managers to shape the future of Canibuild’s AI-powered features and data-driven insights.

The ideal candidate has strong technical understanding (data pipelines, APIs, AI model capabilities), hands-on product experience, and the ability to bring structure and clarity in a fast-paced, evolving startup environment.

Key Responsibilities

  • Define and own the roadmap for data and AI/GenAI initiatives, from early discovery through delivery.
  • Translate business and user needs into data and AI-driven solutions, framing problems and hypotheses clearly.
  • Envision AI and GenAI use cases across Canibuild’s ecosystem — from automations to user-facing intelligence — and scope MVPs or spikes to validate feasibility.
  • Collaborate with data engineers to define and prioritize data pipelines, models, and infrastructure improvements.
  • Work closely with data analysts to ensure relevant KPIs, dashboards, and insights are delivered to stakeholders.
  • Partner with other Product Managers to understand business flows, identify where data sits, and ensure consistent, reliable data usage across the platform.
  • Partner with engineering and design to translate AI and data opportunities into user-centric features.
  • Define and monitor success metrics for AI and data products — ensuring outcomes are measurable and traceable to business impact.
  • Write clear user stories and technical requirements for data and AI-related projects.
  • Balance experimentation and delivery, ensuring short-term wins while building toward long-term AI maturity.
  • Communicate clearly across technical and non-technical stakeholders, simplifying complex ideas and progress updates.
  • Take strong ownership of your domain, working autonomously while keeping the broader team aligned.

Requirements

  • 4+ years of Product Management experience, ideally in SaaS or technology environments.
  • Proven experience working with data, analytics, or AI/ML/GenAI initiatives in a product or technical capacity.
  • Strong understanding of data architecture concepts (data pipelines, APIs, integrations, SQL, ETL/ELT processes).
  • Experience collaborating with data engineers and analysts on delivering data products or AI features.
  • Solid grasp of AI and GenAI capabilities (LLMs, embeddings, retrieval, automation, NLP, etc.) and ability to scope practical use cases.
  • Comfort driving spikes and proofs-of-concept to validate technical feasibility before committing to full builds.
  • Excellent skills in problem framing, hypothesis testing, and prioritization.
  • Strong ability to self-organize, take ownership, and communicate effectively under pressure.
  • Experience working closely with engineering and design teams in Agile environments.
  • Proactive and pragmatic — balances innovation with feasibility.
  • Excellent written and verbal communication skills.
  • Willing to work 6:30 AM – 3:30 PM IST, Monday to Friday
  • Immediate joiners preferred.

Benefits

  • Competitive salary, benefits, and opportunities for growth.
  • A collaborative, fast-paced, and innovative culture that values initiative, ownership, and smart solutions.
  • A remote-first environment with global collaboration.


Position

Product Managers

ML/AI Engineers

Data Analysts

Data Scientist

Data Engineer

Must have skills

Product Management - 4 years

Data analytics - 4 years

SQL - 3 years

Nice to have skills

AI/ML - 3 years

data architecture concepts - 3 years

Data pipelines - 3 years

ETL/ELT processes - 3 years

Integrations - 2 years

AI and GenAI capabilities - 2 years

LLMs - 2 years

Natural Language Processing - 2 years

problem framing - 3 years

Hypothesis Testing - 3 years

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