Product Manager

Allerin builds production AI for enterprises, agentic systems, computer vision, machine learning, and analytics that run in the real world and are measured on real numbers. Our engineering team ships systems like automated defect detection, license plate recognition, and AI-driven analytics for

manufacturing, logistics, retail, and public safety. When we publish a case study, it says things like "false positives down 85 percent", because our clients measure whether it works, and so do we.

We are hiring a Product Manager to own one of our AI products end to end, the problem, the users, the roadmap, and the release. This is a hands-on product role at a company that runs several bets at once, so the product you own will evolve. What will not change is the nature of the work: hard,

technical, and real.

AI products fail differently from ordinary software. A model can be right 80 percent of the time while the client expects to go live next week. The judgment calls in that gap, what ships, what waits, what needs a guardrail, are the core of this job.

What you will do

- Own an AI, ML, or computer-vision product end to end: problem, users, roadmap, release

- Set the KPI a release has to move, and hold the gate when it does not clear it

- Write specs engineers trust, and reason credibly about architecture, cost, and latency

- Design for the failure modes, not just the demo: edge cases, false positives, the long tail

- Ship against evals and real metrics, and build the guardrails that make a demo enterprise-ready

- Tie the work to numbers the business actually feels, and report honestly on what is on track

What we look for

- The judgment to know what to build, and the honesty to kill your own idea when the data says so

- A real understanding that AI systems are probabilistic, not features that simply work or do not

- The habit of prototyping your own ideas with AI tools instead of delegating every question

- Plain, direct communication, especially when something is slipping

We hire for ability, not years. A candidate with three years and something real to show beats a candidate with eight years and a title. We do not require certifications, and we read what you write more carefully than where you worked.

What you get

- End-to-end ownership of a real AI product, with the authority that word implies

- Enterprise clients, production stakes, and problems that are genuinely hard

- A senior engineering team that judges ideas on evidence

- No two months that look the same

Qualifications

• Product management skills: experience owning product roadmap, requirements, and lifecycle for software or AI-powered solutions.
• Technical and data skills: understanding of AI/ML concepts, data analytics, and modern software development practices (experience with agentic systems, computer vision, or analytics is a plus).
• Business and strategy skills: ability to define KPIs, evaluate trade-offs, and align product decisions with measurable business outcomes.
• Collaboration and communication skills: strong stakeholder management, clear written and verbal communication, and ability to work effectively with cross-functional teams.
• User and market understanding: experience in customer research, requirements gathering, and translating user needs into product features.
• Organizational skills: strong prioritization, time management, and comfort working in fast-paced, iterative environments.
• Education: bachelor’s degree in Engineering, Computer Science, Business, or a related field; a master’s degree or MBA is an advantage.
• Experience: prior product management experience in tech, SaaS, or AI-focused companies; experience with enterprise clients or public agencies is beneficial.