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Salary: USD 218,025 - 256,500 / annual
Coinbase's Office of the CTO is seeking a Forward Deployed Engineer to embed within the Finance organization (FP&A & Treasury) and drive AI-powered automation across financial workflows. You will work directly with FP&A and Treasury leadership to identify high-value automation opportunities, prototype solutions using Coinbase's existing AI platform, and own the Finance automation roadmap.
Key responsibilities include:
- Embedding with FP&A and Treasury teams to understand complex workflows such as period-end close, variance analysis, GL reconciliation, multi-entity consolidation, and liquidity stress-testing before designing solutions.
- Rapidly prototyping automation using Coinbase's AI platform as the foundation, with a bias toward leveraging existing tools before recommending new builds.
- Owning the Finance automation roadmap in partnership with the VP of FP&A & Treasury, translating financial workflows into clear engineering requirements and communicating engineering constraints back to stakeholders.
- Defining build-vs-buy strategy for Finance tooling, evaluating internal development, partner adoption, vendor procurement, or retirement of tools.
- Ensuring all automated financial outputs are traceable, reviewable, and auditor-defensible, with SOX compliance, segregation of duties, and human-in-the-loop controls as core design principles.
- Driving adoption through brown-bags, prototype walkthroughs, and feedback loops that bring Finance teams along the journey.
Required experience includes 5+ years of software engineering shipping production systems in ambiguous, stakeholder-heavy environments. You must have hands-on experience deploying LLM-based applications, including prompt engineering, hallucination guardrails, and human-in-the-loop design for high-stakes outputs. Familiarity with financial systems (ERP platforms like NetSuite/Workday, reconciliation logic, trial balances, SOX environments) is essential. Experience in Forward Deployed Engineering, Solutions Engineering, or embedded technical advisory roles—ideally in fintech or enterprise automation—is strongly preferred. Multi-agent orchestration concepts and responsible AI practices are important.
