Forward Deployed Engineer (Remote – US Time Zones)

Location: Remote, with strong overlap to US time zones (EST–PST) At Speedy Labs , we help manufacturers, distributors, and buying groups ditch error-prone spreadsheets and recover millions in missed rebate opportunities with AI-powered rebate management. Our platform connects to customer data, surfaces margin-positive plays, and gives finance and commercial teams the tools they need to manage deductions, rebates, and revenue with confidence. If you want to work on real customer problems, ship production code, and see your work show up directly in your customers’ P&L, this might be your spot. --- About the Role We’re looking for a Forward Deployed Engineer to work at the intersection of engineering, data, and customer outcomes . This is a fully remote role. You’ll partner closely with our customers’ finance, pricing, and IT teams to design, implement, and launch solutions on top of Speedy’s rebate platform. One day you might be mapping a complex rebate program for a buying group; the next, you’re standing up a data pipeline into a customer’s ERP and validating calculations with their finance team. You’ll own projects end-to-end: understanding the business problem, designing the technical approach, implementing integrations and configurations, and ensuring customers are successful in production. --- What You’ll Do Lead technical onboarding and implementations for new customers, from discovery calls through go-live. Design and build integrations between Speedy and customer systems (ERPs, CRMs, data warehouses, rebate trackers) using APIs, webhooks, and scheduled jobs. Configure the Speedy platform to reflect each customer’s rebate programs, contracts, and workflows , including data models, rules, and reporting. Build and maintain Python scripts/services for data ingestion, transformation, validation, and reconciliation. Work directly with customer stakeholders (Finance, Pricing, Procurement, RevOps) to translate fuzzy requirements into clear specs and implementation plans. Debug gnarly issues across data, configuration, and code — logs, SQL, notebooks, whatever it takes to get to root cause. Collaborate with our core product and backend teams to harden and generalize patterns from customer projects into reusable platform features. Create implementation playbooks, runbooks, and internal tooling so the next deployment is smoother than the last. Act as the voice of the customer internally, feeding structured insights back into product discovery and roadmap. --- What You’ll Bring Strong coding skills in Python (Django or similar framework experience is a plus). Solid knowledge of SQL and relational databases (PostgreSQL preferred) — you’re comfortable writing complex joins, debugging data issues, and reasoning about schemas. Experience working with REST APIs (GraphQL a plus) and integrating third-party systems. Hands-on experience with data workflows : ETL pipelines, CSV/Excel imports, data validation, and schema mapping. Familiarity with cloud infrastructure (AWS preferred) and modern deployment practices (Docker, CI/CD, basic observability). Ability to map messy real-world business processes into structured data models and system behavior . Excellent communication skills — you can talk with a CFO about margins and with an engineer about services and queues. 3+ years in a software engineering, data engineering, or implementation engineering role (startup or B2B SaaS experience is a plus). Bonus points for: Experience in manufacturing, distribution, wholesale, pharma, or other rebate-heavy industries . Prior work with ERPs or revenue/financial systems. Comfort working with BI tools or dashboards. --- You’ll Thrive Here If You like talking to customers as much as you like writing code . Ambiguous business problems energize you — you enjoy untangling them and proposing clear, opinionated solutions. You’re happiest when you own projects end-to-end , not just a ticket in a queue. You’re comfortable in a fast-moving startup : priorities shift, feedback loops are short, and “done” is better than “perfect.” You care deeply about correctness — especially when you’re touching revenue, margins, and payments. You enjoy building the systems, templates, and playbooks that make future implementations 10x easier.