Staff Forward Deployed Engineer, AI-Powered Work

Intuit’s AI-Powered Work team helps employees redesign how work gets done with AI. We work with enterprise functions to understand their real problems, build useful solutions, and scale what works. We are looking for engineers who can move from an ambiguous business need to a working prototype and then own the path to a reliable production outcome. As a Staff Forward Deployed Engineer, you will embed with business partners and own a complex workflow from discovery and technical scoping through implementation, production rollout, and sustained adoption. You will combine deep engineering skills with broad product thinking: understanding the problem, testing assumptions quickly, making delivery tradeoffs, and building reusable capabilities with the broader team. Responsibilities Understand how employees work today, including decisions, handoffs, source systems, and exceptions. Partner with business owners and product leaders to select high-value problems, define a measurable baseline and success criteria, and sequence delivery around dependencies and data readiness. Build and demonstrate prototypes early to test the riskiest assumptions with users. Use evidence to refine requirements and redesign the workflow, choosing where AI, deterministic code, or human judgment best serves the outcome. Write production software across the needed layers: user experiences, services, agents, data access, and integrations. Connect enterprise systems through approved APIs and tool interfaces, including Model Context Protocol where appropriate. Ground solutions in relevant knowledge and business data. Implement permissions, provenance, structured outputs, and approval steps so users can understand results and retain control over consequential actions. Create task-level evaluations with domain experts, including ambiguous inputs and failure cases. Establish regression tests and release criteria; add monitoring, recovery paths, and deployment controls. Investigate production issues and balance quality, reliability, latency, and cost. Own delivery through sustained adoption. Work with business partners on rollout, training, feedback, documentation, and a clear ongoing support model. Measure workflow completion, output quality, cycle time, and user effort, and communicate demonstrated outcomes and remaining limitations. Lead solution design and technical decisions within your workstream, reviewing architecture with the Principal Engineer and platform teams. Mentor engineers, strengthen code and design reviews, and turn deployment lessons into reusable components and evidence-backed platform improvements. Qualifications A record of independently delivering complex production software from an unclear problem through launch and iteration with 7+ years of experience, with strong technical ownership and measurable outcomes. Deep hands-on programming and system-design skills in Python, Java, TypeScript, or comparable languages. Experience building cloud services, integrating APIs and data systems, and debugging reliability and performance problems across system boundaries. Practical experience building AI-enabled applications or agents, with an understanding of retrieval, tool execution, evaluations, and when model outputs require validation. Strong product judgment: you can uncover the underlying need with nontechnical partners, define requirements and success measures, prioritize scope, and make tradeoffs across user value, delivery speed, and technical risk. You communicate clearly through writing and working demonstrations. Staff-level technical leadership demonstrated through ownership of a complex capability or workstream, cross-team influence, thoughtful design and code reviews, and mentoring that helps other engineers deliver maintainable software. Experience with enterprise workflows, full-stack product development, SaaS integrations, or secure agent deployment is valuable. Prior FDE titles or consulting experience are not required. Success means b