Magnasoft is twenty years into building one of the world’s deepest
geospatial data assets — and is now turning that asset into AI-powered software
products. We have the data, the domain, and the customer relationships, and our
first product is live in beta with early deployments validated and commercial
traction building. What we’re building next is the engineering organization
that turns this from a services company into an AI-product company.
Today, that AI/ML engineering work runs through a single person: our
VP & Head of Technology. This role exists to change that. As Principal
AI Engineer, you become the most senior engineer in the AI org and the
technical owner of how we build — the architecture, the delivery, and the
engineering craft of the team. This is a player-coach seat: you set the
technical direction and you stay in the code. You are not inheriting a
mature platform to maintain — you are scaling it from a robust foundation.
If you want to be one slice of a large, settled ML org, this isn’t
it. If you’ve drifted away from the keyboard and want a pure management seat,
this isn’t it either. If you want to define — and personally build — the
technical spine of a company at its inflection point, read on.
What you’ll own
Architecture & technical
direction. You own the architecture of the ML
systems behind our product portfolio — a shared computer-vision / OCR /
human-in-the-loop engine applied across multiple product domains. A key
architectural mandate: design the path from periodically-retrained static models
toward models that improve continuously from a production feedback signal,
with the right safety gates rather than a manual blessing on every release.
Hands-on engineering. You write production code — and not only model code. You build the product
code the models live in: the AI backend that runs the
📌 Principle AI Engineer (Bengaluru)
🏢 Magnasoft Consulting India
📍 Bengaluru
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