Forward Deployed Engineer

Bring the Spherecast Platform, our real-time operating system for global consumer goods supply chains, into customers’ daily operations. Agnes, our AI Supply Chain Manager, runs on this foundation to evaluate production, purchasing, and inventory decisions and execute approved actions in their ERP.

As a Senior Forward Deployed Engineer, you’ll own getting Spherecast live and delivering value for the brands you work with. You’ll work directly with supply chain operators and customer IT teams, understand how their business runs, connect their data, configure their workflows, and ship the code needed to make the implementation successful.

Each brand you own will know you as its primary technical partner. You’ll drive the work from discovery through go-live and ongoing adoption, with the engineering judgment to solve problems yourself and bring in the right specialist when needed.

In a typical week, you might move a customer from file uploads to Snowflake, investigate why inventory numbers don’t reconcile, map how goods move between manufacturers and warehouses, or build a supplier performance dashboard.

In this role, you will:

• Own implementations end to end. Lead technical discovery, define milestones and acceptance criteria, run customer working sessions, and drive deployments through validation, go-live, and stabilization.

• Make customer data reliable. Set up and operate integrations using our existing connectors and infrastructure. Build customer-specific mappings and transformations, configure file and warehouse connections, and resolve data quality and synchronization issues.

• Translate supply chains into software. Work with operators to map suppliers, manufacturers, warehouses, and sales channels. Configure planning parameters such as lead times, safety stock, minimum order quantities, and replenishment rules.

• Ship product improvements. Turn customer needs into concrete requirements and build scoped features, dashboards, workflow improvements, and fixes across the backend and frontend. Align feature scope and design with our product lead before building.

• Drive customer progress. Keep milestones, blockers, dependencies, and next steps clear. Follow up with customer stakeholders, coordinate internal work, and communicate progress and risks every week.

• Own activation and ongoing technical success. Validate outputs with customers, help teams adopt their workflows, and stay accountable for resolving issues after launch.

• Make each implementation easier than the last. Turn repeated work into reusable tooling, configuration, documentation, and automation that helps the team support more brands.

You’ll work closely with product and engineering. Our integrations engineer owns shared connectors and the infrastructure for supporting new ERPs. You’ll use that foundation to own each customer’s data setup and implementation. Product engineers own core capabilities and help resolve deeper product issues; you remain the customer’s technical owner throughout.

• Have shipped and operated production software, with strong Python and SQL skills and the ability to work across APIs, data pipelines, and frontend interfaces.

• Can take an ambiguous customer problem from discovery to a working solution, including scoping, implementation, testing, and rollout.

• Are comfortable leading customer calls, asking precise questions, explaining technical tradeoffs, and setting clear expectations.

• Debug systematically across source systems, data transformations, application logic, and the user interface.

• Can manage several customer implementations at different stages while keeping commitments and priorities clear.

• Use AI coding tools effectively and take responsibility for the quality and reliability of what you ship.

• Want to work on-site with an ambitious team in New York City, move quickly, work hard, and take substantial ownership.

Spherecast is building the AI-native Operating System for Consumer Goods Supply Chains.

The Spherecast Platform brings demand, inventory, materials, capacity, costs, and business rules into one real-time operating context. It gives teams a single place to plan, evaluate tradeoffs, and execute the decisions that move physical goods.

Agnes, our AI Supply Chain Manager, runs on top of this foundation. It evaluates thousands of feasible options in seconds to decide what to produce, where to make it, and how to move it through factories, warehouses, and channels. Teams set the objectives and guardrails; Agnes turns them into approved actions in the ERP.

Our ambition is to make the physical flow of goods as programmable as code. When we succeed, every consumer product you touch will run on the Spherecast stack: planned in Spherecast OS, executed through Spherecast Rails, and optimized by the shared Spherecast Network.

Oracle made business data programmable. Spherecast makes the physical economy programmable.

Join us in the trenches in New York City to build the AI-native Operating System for Consumer Goods Supply Chains.

Be part of building the next trillion-dollar company.