We’re delighted to announce that Mélissa Djuimo and Matthieu Allegre, two of our Engineering Program Managers (EPM), were invited to the Tech Lead Corner podcast to share their experience and discuss the specific EPM role at Pigment.
🎧 Tech Lead Corner | Mélissa Djuimo and Matthieu Allègre - Being EPM at Pigment.
At Pigment, we provide a central platform for organizations to model and plan using their most valuable data. As part of that mission, enabling predictive insights is key. Our first implementation of predictions worked well for smaller datasets, but as more users began applying the feature to larger and more complex data models, we quickly hit the limits of a single-machine setup in terms of memory and compute.
To address this, we redesigned our infrastructure around a distributed Dask cluster, allowing us to scale horizontally and support much larger workloads. In this post, we’ll share the architecture of our new solution and key takeaways from adopting Dask in production.
Agentic AI, in which one or multiple AI agents can pursue goals autonomously or collaboratively, represents a new frontier in generative AI. Unlike traditional large language models (LLMs) that operate independently, these systems combine specialized agents with unique roles to handle complex, open-ended tasks. Here, we’ll explore how Pigment uses this approach for data analysis, empowering clients to gain deeper insights.
Unit tests, integration tests, end-to-end tests — like many modern development teams, at Pigment, we rely heavily on these methods to minimize the risk of functional regressions in our codebase. In this post, we'll explore how we added image snapshots to our Cypress end-to-end tests as an extra safeguard for catching visual regressions.
Our R&D team is hard at work tackling the challenges that come with building a modern business planning platform. Engineering Program Manager Chaimaa E. and Tech Lead Benjamin Hewins, recently spoke with Elliot Kipling and Enginears to share their insights on Pigment's engineering team, culture, and the technical problems they're solving each day.