
51 - 200 employees
⥠Energy
âď¸ SaaS
đŚ Logistics
đ° Corporate round on 2024-08
Energy ⢠SaaS ⢠Logistics
Gravitate is an AI-native software platform that connects and optimizes the refined fuels supply chain. It provides real-time supply optimization, autonomous dispatch, a transportation management system purpose-built for fuel haulers, an integration hub (Crossroads) for sharing inventory/orders/ETAs across refiners, terminals, carriers and retailers, an online selling platform for bulk fuel, and a rules-based pricing engine. Gravitate's products aim to automate sourcing, pricing, freight billing and dispatch workflows so fuel operators capture more margin and reduce manual coordination.
đ September 18
Where this job comes from
Posted on Gravitate's careers page, not through a job board
First seen by Remote Rocketship September 18
Still open on Gravitate's site. Checked 6 hours ago.

51 - 200 employees
⥠Energy
âď¸ SaaS
đŚ Logistics
đ° Corporate round on 2024-08
Energy ⢠SaaS ⢠Logistics
Gravitate is an AI-native software platform that connects and optimizes the refined fuels supply chain. It provides real-time supply optimization, autonomous dispatch, a transportation management system purpose-built for fuel haulers, an integration hub (Crossroads) for sharing inventory/orders/ETAs across refiners, terminals, carriers and retailers, an online selling platform for bulk fuel, and a rules-based pricing engine. Gravitate's products aim to automate sourcing, pricing, freight billing and dispatch workflows so fuel operators capture more margin and reduce manual coordination.
⢠Drive delivery of large backend features end-to-end ⢠Break large projects into manageable plans, estimate work, and raise risks early ⢠Lead technical design for complex features and evaluate performance, maintainability, and cost trade-offs ⢠Document technical decisions and design for extensibility ⢠Own a significant product area or full service, including reliability, performance, and evolution ⢠Build and operate Python services, APIs, and MongoDB data models ⢠Deploy and operate systems on Kubernetes across GCP and Azure ⢠Debug and resolve medium-to-large production issues ⢠Identify root causes and drive response and recovery ⢠Drive monitoring, observability, and performance health ⢠Review code and technical designs with constructive feedback ⢠Mentor junior and mid-level engineers ⢠Partner with product on medium-to-large features and help shape product decisions ⢠Write technical documents and communicate complex topics to non-technical stakeholders ⢠Proactively unblock team members and make pragmatic speed-versus-quality trade-offs ⢠Help shape team culture and engineering practices ⢠Work with an AI-enabled development workflow and help build supporting harnesses
⢠5+ years of professional software engineering experience building and operating production backend systems ⢠Deep expertise in multiple areas of a backend stack ⢠Python preferred as a primary server-side language ⢠Experience with API design, data modeling, and automated testing ⢠Demonstrated track record of delivering large features end-to-end with moderate unknowns ⢠Experience owning a service or major product area in production, including reliability and performance ⢠Strong debugging and troubleshooting skills on medium-to-large issues ⢠Comfortable participating in on-call for owned systems ⢠Working knowledge of infrastructure, security, observability, CI/CD, and deployment practices ⢠Experience mentoring junior and mid-level engineers ⢠Experience giving high-quality code review feedback ⢠Strong written and verbal communication skills ⢠Ability to produce clear medium-to-large technical documents ⢠Ability to explain trade-offs to non-technical stakeholders ⢠Openness to utilizing and becoming an expert in AI-assisted development ⢠Nice to have: Python, MongoDB, Kubernetes, GCP or Azure ⢠Nice to have: React/TypeScript experience ⢠Nice to have: B2B SaaS or enterprise software experience ⢠Nice to have: logistics, supply chain, or energy/fuel domain background ⢠Nice to have: performance and scale work with large data volumes, query optimization, caching, and profiling ⢠Nice to have: AI engineering experience with production agentic systems and ML/operations models
⢠Fully remote work arrangement
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