> Markdown version of [/jobs/ext/1504838-forward-deployed-engineer](https://www.wearedevelopers.com/jobs/ext/1504838-forward-deployed-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Forward Deployed Engineer - **Company:** Intuit Inc. - **Location:** Mountain View, CA, United States - **Experience:** Expert - **Salary:** $202,500.0 - $274,000.0 - **Contract:** Franchise - **Skills:** Artificial Intelligence, Software as a Service, Python (Programming Language), SQL Databases, Data Streaming, Systems Integration, Graphql, Virtual Agents, Api Design, Restful APIs, Webhooks - **Published:** July 30, 2026 - **Apply:** https://dejobs.org/x/x/C4BEA980D50E478995C7E9DB0B01A070/job/ ## About the Role * 5+ years in Forward Deployed Engineering, Solutions Engineering, Sales Engineering, technical consulting, or a comparable hands-on, customer-embedded engineering role (scope and level matched to experience - see Levels & Compensation below). * Deep experience with REST APIs, GraphQL, webhooks, SQL, and enterprise integrations. * Strong technical fluency and the ability to collaborate deeply with Product Managers and Engineers as a peer, not a hand-off. * A track record of managing multiple technical deployments simultaneously under delivery pressure. * Comfort leading technical troubleshooting calls with customers and internal IT teams. * Comfortable operating on both sides of the signature - building a credible proof-of-value under sales-cycle time pressure, and running that same system reliably in production afterward. * You default to automation - you use AI and modern tooling to move faster, document better, and scale your own impact. * Demonstrated ability to translate ambiguity into executable requirements, and to communicate insights clearly to both engineers and executives. * Strong commercial awareness, stakeholder management, and the ability to operate effectively under delivery and revenue pressure. Preferred * Background in high-growth SaaS, applied AI, or fintech/ERP/accounting-adjacent domains. * Domain experience in one of our priority verticals - construction (job costing, WIP, retainage), nonprofit (fund accounting, grant and donor compliance), manufacturing (inventory, cost accounting, production workflows), wealth management (client billing, compliance/regulatory reporting, investment accounting), health care (revenue cycle, compliance-heavy financial operations), franchise (zee governance, zor performance), or field services (job/work-order costing, scheduling-linked billing). You don't need more than one, but depth in any single vertical materially shortens ramp-up on real customer engagements. * Non-traditional paths are a plus: veterans, former management consultants, competitive programmers, and PhDs have historically made excellent FDEs. * Prior experience embedded at a customer site for a multi-month deployment (implementation consulting, forward-deployed, or field engineering background). ## Description Intuit Enterprise Suite is how the world's fastest-growing mid-market and enterprise finance teams run their books, close their quarter, and put AI agents to work on real accounting operations - not demos. Forward Deployed Engineers (FDEs) are the team that makes that real: embedded with our customers, shipping production automation, and turning "AI pilot" into "AI in the general ledger." This isn't a traditional sales engineering role, and it isn't a traditional product engineering role either. FDEs report into Engineering, work shoulder-to-shoulder with Sales and Account Management on the deals and renewals that matter most, and own the last mile between what Core Engineering ships and what a specific customer actually runs. You'll sit at the intersection of engineering, applied AI, and enterprise finance, and you'll be judged on one thing: did the customer's business measurably change because you were in the room. Responsibilities What you'll do Pre-sale: build the proof that wins the deal * Get hands-on with prospects before there's a contract: build a working proof-of-value directly in (or against a realistic replica of) the prospect's own data and systems - real integrations and real output, not a scripted demo. * Partner with Account Executives from first technical touch: run discovery with the prospect's finance and IT teams to understand their chart of accounts, systems, and process gaps well enough to build against them. * Lead the technical evaluation: architecture and security/compliance reviews, integration feasibility, and technical RFP responses with the prospect's IT and controllership teams. * Build the technical narrative and ROI case alongside Sales, and present it directly to economic buyers - CFOs and Controllers - as part of the deal cycle. Your proof-of-value is very often what gets the deal signed. * Flag technical or data-readiness risk early, so Sales scopes and prices the deal accurately and nothing you built pre-sale becomes a surprise post-signature., * Architect and deploy customer-specific configurations of AI Agents that automate complex accounting processes - strengthening internal controls, closing books faster, and removing manual work from real customer environments. * Perform deep technical troubleshooting: review and edit Python, write SQL for integrations, and diagnose configuration issues across customer systems. * Serve as the functional and technical escalation point for issues involving integrations, data flows, and automation logic - including reviewing and optimizing SQL-based validations and API-driven workflows. * Maintain SLAs for response and resolution; document issues comprehensively and escalate to Engineering with complete context. Post-sale: own the customer relationship and drive expansion * Lead high-impact transformation engagements with enterprise finance teams - diagnosing operational bottlenecks and identifying where AI Agents create the most leverage. * Act as the primary technical point of contact across implementations, engaging directly with CFOs, Controllers, and accounting leaders. * Guide and train customer teams through workflow redesign, change management, and the value realization required to scale AI Agent adoption across their organization - and carry that same proof-of-value discipline into expansion and renewal conversations. * Travel to customer sites as needed (up to 70%) for pre-sale technical evaluation, hands-on deployment, training, and adoption workshops. Ongoing: shape the product and the playbook * Be the Voice of the Customer: surface technical feedback, integration requirements, and product gaps to Product and Core Engineering - as input to their roadmap, not a substitute for it. * Partner with Product Management on learnings from onsite discovery sessions to design workflows centered on AI Agent deployment and business outcomes. * Build the playbook: create implementation guides, expansion frameworks, and reusable assets so every deployment makes the next one faster. * Educate customers and internal teams on the strategic value of AI-enabled workflow transformation and best practices for building durable AI Agents. Where this role sits FDEs report into Engineering, not Sales - but this is very much a field role, spanning both sides of the signature, and the two partnerships below are the job as much as the code is. Your partnership with Sales & Account Management * You're the technical face of Enterprise Suite in the field, on both sides of the deal: Account Executives pull you in pre-sale to build the proof-of-value that wins the technical evaluation, and Customer Success pulls you in post-sale for QBRs, renewals, and expansion. * Deals and renewals in this business run on proof, not promises - you're the one who produces it, first as a working pilot in the sales cycle, then as a live production system afterward. That makes you directly responsible for de-risking the pipeline, even though you don't carry a number yourself. * You'll work daily with Account Executives and Customer Success on the accounts you're assigned to; you won't be measured on bookings, but expect to be in the room for the technical parts of both the sale and the renewal. Your partnership with Core Engineering * You build on top of what Core Engineering ships - you're not a parallel path to the platform roadmap, and this role doesn't re-architect the core product. * Your job is the last-mile layer: wiring existing AI Agent capabilities into one customer's specific data, workflows, and edge cases, fast enough to prove value inside a live deal. * In return, you feed Core Engineering structured signal - the patterns that show up across multiple customers - so they can decide what to productize. 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