Principal Software Engineer, Data

Description

Why We Built the company: Supply chains are more critical and complex than ever. Every day, large enterprises navigate trillions of possible decisions that could impact the bottom line. Powerful algorithms and AI can address these problems, yet most organizations struggle to leverage supply chain AI at scale. The current SCM technologies are either rigid, limited-scope point solutions or custom solutions built in-house, which demand immense expertise and investment.

That is…until now.

Enter the company : the company is an enterprise AI platform built specifically for supply chains, offering the best of both worlds:

Out-of-the-box AI solutions for optimizing networks, allocating inventory, scheduling routes, planning fulfillment capacity, promising orders, propagating demand, building predictions, analyzing scenarios, and more, plus

A platform-first approach that empowers both business and technical users with end-to-end product composability, leveraging no-code tools, their own code, or even forking our code to build and refine supply chain decision intelligence

With the company, enterprises no longer have to choose between flexibility and speed, they get both.

The Mission: We’re building a new era in supply chain with the team best equipped to lead it. With over 20 years at the intersection of supply chain and algorithms, we developed a deep conviction that global supply chains needed something like the company. Since our inception in December 2021, that conviction has been validated time and time again.

We can’t wait to see what our customers, both current and future, are empowered to build with us next. Come build with us!

The role: You'll own the data platform that the company's products and AI agents reason over, end to end. The hardest part is the semantic layer: a model of how a customer's supply chain fits together that agents can query reliably. It's a hands-on principal IC role. You'll set the architecture, write much of the code and raise the engineering bar, working directly with our Head of Engineering.

What you'll own

The semantic layer: entity models, ontology and knowledge graph, through to the APIs apps and agents query

Data foundations: enterprise ingestion and data contracts, schema evolution, orchestration, storage and query

Correctness and reliability in a multi-tenant product, including recovery from hard incidents

Technical direction through RFCs, design reviews and your own code, and mentoring senior engineers

Requirements

• Data platforms or semantic layers you personally built and owned in production: knowledge graphs, metadata or metrics layers, entity models
• First-principles systems reasoning: durability, failure and recovery, and where your design breaks at scale
• Something you built from zero at a startup and took to production scale
• You still write production code and work fluently with AI coding tools
• Clear communication and the presence to lead senior engineers without authority
• Good to have: Property graphs or RDF/SPARQL; entity resolution or master data; Spark, Kafka, Flink or Iceberg; durable execution; systems-performance depth; supply-chain data.
• Location: Bengaluru or Chennai, hybrid; returners welcome. Open to Europe for the right person.
• How we hire: Recruiter screen, an exploration call with engineering leadership, then a deep dive on a system you built. Next, a take-home build using any AI tools you like, which you present to a senior engineering panel. We close with a leadership and values conversation.