Senior Forward Deployed Engineer

Planful

Posted 1mo ago

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Own customer rollouts end to end — data integration, model build-out, validation, and production cutover — as the primary technical owner.
Build AI-driven automated test harnesses to validate every new product release against real customer use cases and models, catching regressions before they reach customers.
Build and maintain data integrations between customer source systems (ERP, GL, data warehouses) and our platform, treating them as durable, version-controlled engineering deliverables rather than throwaway scripts.
Translate real-world requirements in financial and operational modeling into correct, performant models on the platform.
Diagnose and resolve data, performance, and correctness issues — often deep in SQL, source data, and consolidation logic.
Ship bug fixes and feature extensions directly against the platform — make targeted product changes to unblock customers and close gaps surfaced in the field, rather than only filing tickets and waiting on core engineering.
Act as the feedback loop to product and engineering: surface friction, propose fixes, and where warranted, build them.
Partner with customer stakeholders across finance and operations, earning trust as someone who understands their domain and can make the software do what they need.

10+ years in software engineering, with meaningful time spent on or around an EPM/CPM/financial planning product.
Direct experience with a platform such as OneStream, Vena, Prophix, Anaplan, Planful, or TM1/ Planning Analytics — as an engineer, solutions architect, or technically deep implementer.
Proficiency in a modern application language — Java, C#, or TypeScript — with the ability to read, extend, and ship changes in a production codebase.
Experience building automated test frameworks or harnesses, ideally using AI or LLM-based approaches to generate, execute, and evaluate test cases at scale.
Strong SQL and database fundamentals: schema design, query performance, joins and aggregation semantics, and reasoning about data at scale.
Integration experience with ERP/GL systems and data warehouses (e.g., NetSuite, SAP, Oracle, Snowflake, BigQuery).
A customer-facing disposition — you can run a working session, absorb domain nuance, and communicate clearly with finance stakeholders who don't think in code.
Sound judgment on correctness and auditability: you understand that in financial systems a wrong number is worse than a slow one.
Understanding of financial consolidation, multi-entity / multi-currency, allocations, or driver-based planning.
Domain exposure to CPG or manufacturing operational planning.
Experience with AI-assisted or AI-native tooling in a production data context.
A track record of turning repeated customer pain into product improvements.

Skills