Job description

Forward Deployed Engineers (FDEs) are how Intuit Enterprise Suite turns “AI pilot” into “AI in the general ledger” embedded with our largest mid-market and enterprise finance customers, shipping production automation instead of demos. As the Manager 3 (M3) leading a Forward Deployed Engineering pod, you own the outcomes of that team: the technical direction of its engagements, the quality of what it ships, the health of its customer relationships, and the growth of the engineers on it. This is a player-coach leadership role. You'll still be technical enough to unblock your team on a production incident or a stalled integration, but your primary job is building a pod that can carry multiple concurrent, high-stakes deployments without you being the bottleneck and being the executive-level technical face of your accounts when the moment calls for it. Responsibilities Lead the pod • Hire, coach, and manage a team of Forward Deployed Engineers; set the technical bar for the group and own their career growth and performance. • Own technical direction, customer delivery outcomes, engineering quality, and prioritization across every active engagement in your pod. • Decide how incoming requests get staffed including whether a given ask belongs in Sales, Platform, or FDE and balance pod capacity against the deployment pipeline. • Run (or drive) the pod's prioritization and requirements review cadence so concurrent engagements are sequenced against real capacity, not wishful thinking. Own delivery and customer relationships • Serve as the executive-level escalation point for your pod's deployments, architecture, integration, and data-flow issues that need a manager's judgment or authority to unblock. • Engage directly with CFOs, Controllers, and IT leaders on your team's most strategic accounts, particularly pre-sale proof-of-value, technical evaluations, and renewal/expansion conversations. • Own SLA accountability for your pod's response and resolution commitments; make sure issues are documented and escalated to Core Engineering with complete context. • Guide your engineers on turning agentic AI capabilities into customer-specific production deployments that automate accounting processes and strengthen internal controls. Partner across the business • Represent FDE with Sales, Account Management, and Customer Success leadership on deal risk, renewal health, and expansion pipeline for your pod's accounts. You don't carry a number, but you're accountable for de-risking it. • Partner with Core Engineering and Product leadership so field learnings sharpen the roadmap FDE work should never duplicate or bypass the core platform. • Report pod health, SLA performance, and delivery risk to engineering and go-to-market leadership. Build the practice • Build and maintain the implementation playbook guides, expansion frameworks, and reusable assets so every deployment is faster than the last. • Set the hiring bar and run the interview loop for the FDE ladder in your org: technical craft, real customer exposure, and a track record of shipping under ambiguity. Qualifications • 8+ years in Forward Deployed Engineering, Solutions Engineering, Sales Engineering, technical consulting, or a comparable customer-embedded engineering role. • 2+ years directly managing engineers, ideally in a customer-facing, field, or forward-deployed capacity. • • Demonstrated experience leading positive change, empowering people, cultivating product technology visions and innovative solutions, and fostering effective FDE teams. • Deep experience with REST APIs, GraphQL, webhooks, SQL, and enterprise integrations. • Deep experience with Agentic AI: LangChain, LangGraph, MCP servers, multi-agent, RAG, vector stores, hybrid retrieval • Experience with LLMs & tooling: OpenAI, Gemini, Anthropic; GitHub Copilot, Gemini Code Assist; prompt engineering • Strong technical fluency and the ability to collaborate deeply with Product Managers and Engineers as a peer, not a hand-off. • A track record leading multiple concurrent technical deployments under real delivery and revenue pressure. • Comfort being the executive-level technical face of a program presenting to CFOs and Controllers, running exec escalations, and defending prioritization calls with GTM leadership. • Demonstrated ability to turn ambiguity into a staffed, sequenced execution plan across a team, not just for yourself. • Strong commercial awareness and stakeholder management across Sales, Product, and Core Engineering. • Background in high-growth SaaS environments. Preferred • Experience managing a field or forward-deployed engineering team specifically, rather than a traditional product engineering team. • Domain experience in accounting/ERP, fintech, or one of Intuit Enterprise Suite's priority verticals: construction, nonprofit, manufacturing, wealth management, health care, franchise, or field services. • Hands-on experience with agentic AI workflows building, configuring, or deploying AI agents in production. • Experience building an interview loop, leveling rubric, or playbook for a technical field-engineering discipline. • 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. • Prior experience embedded at a customer site for a multi-month deployment (implementation consulting, forward-deployed, or field engineering background). Intuit provides a competitive compensation package with a strong pay for performance rewards approach. This position may be eligible for a cash bonus, equity rewards and benefits, in accordance with our applicable plans and programs (see more about our compensation and benefits at Intuit®: Careers | Benefits ). Pay offered is based on factors such as job-related knowledge, skills, experience, and work location. To drive ongoing fair pay for employees, Intuit conducts regular comparisons across categories of ethnicity and gender. The expected base pay range for this position is: Mountain View $244,000 - $330,000

Requirements

Must-haves

Lead the pod
Hire, coach, and manage a team of Forward Deployed Engineers; set the technical bar for the group and own their career growth and performance.
Own technical direction, customer delivery outcomes, engineering quality, and prioritization across every active engagement in your pod.
Decide how incoming requests get staffed including whether a given ask belongs in Sales, Platform, or FDE and balance pod capacity against the deployment pipeline.
Run (or drive) the pod's prioritization and requirements review cadence so concurrent engagements are sequenced against real capacity, not wishful thinking.
Own delivery and customer relationships
Serve as the executive-level escalation point for your pod's deployments, architecture, integration, and data-flow issues that need a manager's judgment or authority to unblock.
Engage directly with CFOs, Controllers, and IT leaders on your team's most strategic accounts, particularly pre-sale proof-of-value, technical evaluations, and renewal/expansion conversations.
Own SLA accountability for your pod's response and resolution commitments; make sure issues are documented and escalated to Core Engineering with complete context.
Guide your engineers on turning agentic AI capabilities into customer-specific production deployments that automate accounting processes and strengthen internal controls.
Partner across the business
Partner with Core Engineering and Product leadership so field learnings sharpen the roadmap FDE work should never duplicate or bypass the core platform.
Report pod health, SLA performance, and delivery risk to engineering and go-to-market leadership.
Build the practice
Build and maintain the implementation playbook guides, expansion frameworks, and reusable assets so every deployment is faster than the last.
Set the hiring bar and run the interview loop for the FDE ladder in your org: technical craft, real customer exposure, and a track record of shipping under ambiguity.
8+ years in Forward Deployed Engineering, Solutions Engineering, Sales Engineering, technical consulting, or a comparable customer-embedded engineering role.
2+ years directly managing engineers, ideally in a customer-facing, field, or forward-deployed capacity.

Nice-to-haves

Experience managing a field or forward-deployed engineering team specifically, rather than a traditional product engineering team.
Hands-on experience with agentic AI workflows building, configuring, or deploying AI agents in production.
Experience building an interview loop, leveling rubric, or playbook for a technical field-engineering discipline.
Background in high-growth SaaS, applied AI, or fintech/ERP/accounting-adjacent domains.
Prior experience embedded at a customer site for a multi-month deployment (implementation consulting, forward-deployed, or field engineering background).
Mountain View $244,000 - $330,000

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