Product Manager (Post-Training Platform & Iterative Architecture)

Product Manager (Post-Training Platform & Iterative Architecture)

Role Overview

We are seeking a deeply technical, executive-level Product Manager to define and drive the product lifecycle for Ethara.AI's RLaaS platform and long-horizon evaluation ecosystems. Boasting a 15+ year career across core software engineering, framework development, and product strategy, you will bridge the gap between complex ML research and scalable enterprise software products.

You possess a deep-rooted understanding of software design patterns and a rich history of leveraging rapid-application frameworks (like Odoo) to quickly build, iterate, and monetize complex, data-driven platforms.

Key Responsibilities

• Product Strategy & Lifecycle: Own the macro product roadmap, monetization strategies, and market positioning for our RLaaS platform, multi-step simulation environments, and human-in-the-loop validation dashboards.
• Rapid-Iteration Framework Architecture: Guide the engineering and design teams on utilizing modular, open-source architectures (like Odoo) to build highly customizable enterprise portals, grading workflows, and backend data layers.
• Authentic SWE Simulation Design: Ensure our evaluation benchmarks (like MILO-Bench) accurately simulate genuine, complex software development cycles—including legacy code refactoring, dependency graphing, and version control conflicts.
• Strategic Client Alignment: Act as the primary interface for product alignment with executive teams at frontier AI labs and Fortune 500 enterprises, translating abstract post-training research into production-ready features.

Qualifications

• Experience: Minimum 15+ years spanning technical product management, software engineering, and platform architecture (specifically in Developer Tools, Enterprise ERPs, MLOps, or complex API ecosystems).
• Framework & SWE Domain Expertise: Expert knowledge of Odoo or closely related rapid-application frameworks, alongside deep foundational roots in core SWE principles (monolithic vs. microservices, relational database design, secure API design).
• AI/ML Fluent: Thorough understanding of post-training paradigms, including Supervised Fine-Tuning (SFT), RLHF, reward modeling, and trajectory evaluation metrics for software engineering agents.
• Executive Communication: Elite ability to draft rigorous, highly technical PRDs and present strategic tech roadmaps clearly to executive stakeholders and external enterprise clients.