Freelance Product Manager

hace 2 semanas

Buenos Aires, Buenos Aires C.F., Argentina Hogarth Worldwide A tiempo completo

A Hybrid working model



We believe the best work happens when we're together, fostering creativity, collaboration, and connection. That's why we've adopted a hybrid approach, with teams in the office around four two a week. If you require accommodations or flexibility, please discuss this with the hiring team during the interview process.



Product Manager — AI‑Assisted Production Platform 

Overview 

You will lead the product strategy and execution for an AI‑assisted production platform that helps creative and production teams blending workflow integration, automation, and applied AI (including computer vision and generative approaches) to reduce cycle time, improve consistency, and minimise rework for the production process. 

You will own the end‑to‑end product lifecycle: shaping the vision, defining the roadmap, aligning stakeholders, and partnering with engineering and applied AI teams to deliver reliable capabilities in a security‑constrained enterprise environment. 

You will not be doing this alone. You will join a collaborative, high‑calibre team of engineers, applied AI/ML experts, delivery partners, and domain specialists who care about building things that work in the real world. The role is hands‑on and high‑impact, but it comes with strong support, kindness, and a shared bias for learning and continuous improvement. 

This role is outcome‑driven. Success is measured by measurable production impact (time saved, adoption, etc.) and by building a platform that teams trust for real work. 

What You'll Do 

Set product vision, strategy, and roadmap 

Define a clear product narrative that connects user outcomes, business impact, and technical direction. Translate discovery into a roadmap that balances quick wins, platform foundations, and long‑term bets. 

Own outcomes and success metrics 

Define measurable goals such as throughput, cycle time reduction, defect rates, adoption, and rework reduction. Instrument the product and use data and qualitative feedback to guide prioritisation and iteration. 

Deeply understand the workflow and integration surface 

Map end‑to‑end production journeys across teams and tools. Define integration requirements with existing workflow systems, asset libraries, and creative tooling APIs. Clarify source‑of‑truth boundaries, sync behaviours, and operational constraints. 

Lead requirements definition 

Partner with users and SMEs to turn problems into well‑scoped requirements, user stories, and acceptance criteria. Define edge cases, fallbacks, and "definition of done" for AI‑assisted steps. 

Partner tightly with engineering and applied AI 

Articulate the what and why and collaborate on the how. Ensure solutions are scalable, maintainable, and resilient under real production load. Drive pragmatic decisions on model usage, evaluation, and human‑in‑the‑loop workflows. 

Run an effective delivery cadence 

Own backlog prioritisation and keep it transparent and ready. Collaborate with programme delivery to support agile ceremonies, clarify scope, and unblock teams. Lead sprint reviews and ensure delivered work meets acceptance criteria and quality bars. 

Steer quality, risk, and governance 

Identify and manage risks, dependencies, and trade‑offs across product, data, and integration work. Drive readiness for audits and operational governance, including traceability and reporting. 

Communicate with clarity across audiences 

Maintain alignment with client stakeholders and internal leadership. Produce crisp documentation: PRDs, decision logs, rollout plans, and release notes. 

What You'll Bring 

Product leadership experience 

5+ years in product management (or equivalent) delivering complex software products, ideally workflow or platform products. Demonstrated ability to lead ambiguous problem spaces from discovery through delivery and adoption. 

Strong technical fluency 

Comfort discussing software architecture, APIs, integration patterns, and operational concerns. Ability to collaborate credibly with engineers and applied AI/ML practitioners. 

Applied AI understanding 

Working knowledge of AI/ML concepts (for example: model evaluation, data quality, uncertainty, human‑in‑the‑loop design, and production monitoring). Practical understanding of where automation works well, where it fails, and how to design safe fallbacks. 

Execution excellence 

Strong prioritisation, backlog management, and stakeholder alignment skills. Experience working in agile teams and shipping iteratively with clear success criteria. 

Communication and influence 

Excellent written and verbal communication, including the ability to simplify complex topics. Confidence engaging stakeholders across product, engineering, design, operations, and leadership. 

Nice to Have 

Experience with creative production workflows, asset pipelines, or design tooling ecosystems. Experience building enterprise software in security‑constrained environments (auditability, access controls, restricted tooling, environment separation). Experience defining quality frameworks for automated outputs (for example: visual diffs, heatmaps, review queues, sampling strategies). Relevant certifications (for example: CSPO) or advanced degrees in a technical discipline. 

#LI-Hybrid

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