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Open nowPosted 31 days agoWe saw it 86 min after it went up

AI Product Stream Lead

Cargoo6 open roles

Where
Yerevan, Armenia
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Your applicationOpen nowAI Product Stream LeadCargoo · Yerevan, Armenia

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The clock on this job

Early applications get read.

12.9% of postings close within 7 days. Measured by our own scanner across the market. Cargoo postings stay open a median of 29 days.

Share of postings closed within
  1. 2.2%1 day
  2. 4.7%3 days
  3. 12.9%7 days
  4. 21.0%14 days
  5. 35.6%30 days
  6. 58.5%60 days
This job: posted 31 days ago

Cargoo median: 29 days open

The posting

Role Purpose

The AI Product Stream Lead defines and delivers AI-powered supply chain solutions that solve real customer and operations problems on the Cargoo platform. You own a product stream end to end, from framing where AI creates value (automation, decision support, agents) to shipping it and proving it works in production.

You lead a cross-functional team, balancing customer value, technical and data feasibility, AI quality and cost, business priorities and delivery timelines. You also help set how Cargoo builds product in an AI-native way.

Key Responsibilities

AI Product Vision & Strategy

  • Shape the stream’s product vision and strategy with stakeholders, in line with Cargoo’s AI strategy and customer needs.
  • Identify and prioritize AI opportunities across freight operations (e.g. exception handling, quoting, document processing, planning and execution support) by value, feasibility and risk.
  • Decide where AI should automate, where it should assist, and where a human must stay in control.
  • Own product decisions, balancing customer value, technical feasibility, AI quality, cost, business priorities and delivery timelines.

Leadership & Delivery

  • Lead the development team through the whole product lifecycle, from discovery to rollout and adoption.
  • Decide scope, schedule and quality, including when an AI feature is good enough to ship and when it needs another iteration.
  • Run fast discovery loops: prototype with AI tools, validate with real users and data, then commit.
  • Make sure the team meets internal policies, data protection rules and responsible-AI standards (incl. EU AI Act awareness).

Product Management & Requirements

  • Create clear Use Cases, Requirements and Business Rules. For AI features, add expected behaviour, edge cases, failure modes and escalation paths.
  • Define success and evaluation criteria for AI features with engineering: accuracy, latency, cost per task and acceptable error rates, backed by representative test sets.
  • Write User Stories and Acceptance Criteria that cover both deterministic logic and probabilistic AI behaviour.
  • Work with engineering and data owners on data readiness: which data we need, its quality, and who owns it.
  • Own and continuously refine the Product Backlog so the team always works on the highest-value opportunities.
  • Track adoption and impact after release (time saved, automation rate, user trust) and feed the learning back into the roadmap.

AI-Native Ways of Working

  • Use AI tools every day for research, specs, prototyping, data analysis and feedback synthesis.
  • Help the team and wider product org adopt AI-assisted delivery practices.

Candidate Profile

Education & Experience

  • 5+ years managing software development projects, strongly preferably as a Product Owner.
  • Proven managerial skills: team leadership, decision-making and conflict resolution.
  • Degree or diploma in Information Technology, Informatics or a related field.

Technical Skills (Must Have)

  • Deep understanding of Agile values, principles and frameworks (Scrum, Kanban, Lean) and the ability to apply them well.
  • Strong analytical skills, comfortable working with data to make product decisions.
  • Solid working understanding of how LLMs and AI agents work, what they are good at, and where they fail (hallucinations, non-determinism, cost, latency).
  • Hands-on, daily use of AI tools in your own work.
  • Fluent English, written and spoken.

Strong Plus

  • Having shipped at least one AI/ML or LLM-based feature to production.
  • Experience defining evaluation criteria or test sets for AI features.
  • Logistics background or experience with logistics solutions.
  • Experience with data products, workflow automation or decision-support systems.

Behavioral Traits

  • Excellent communication with technical and non-technical audiences, including customers, executives, managers and subject matter experts. Able to explain AI trade-offs in plain language.
  • Strong leadership and decision-making, able to guide teams and resolve conflicts.
  • Analytical, structured and value-driven in prioritization. Evidence over hype.
  • Curious and fast-learning, comfortable with ambiguity and quick iteration.
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