Forward Deployed Engineer

MethodHub; Mountain View (CA); On-site; USD 150,000 - 210,000; Full time

Job summary

MethodHub is seeking an embedded Forward Deployed Engineer to join our Enterprise Suite team. You will be seconded into customer environments to ship production automation, proving AI-driven workflows in the general ledger context.

You will work across engineering, sales, and account management, owning the last-mile between core tech and customer reality, while traveling up to 70% to sites.

Qualifications

• Hands-on with Python and SQL to build customer proofs-of-value.
• Lead technical evaluation, architecture reviews, and RFP responses with customer teams.
• Provide pre-sale and post-sale technical support and guidance.

Responsibilities

• Build a working proof-of-value in prospect data and systems.
• Partner with Account Executives to run discovery and tailor solutions.
• Deploy customer-specific AI Agent configurations and validate integrations.
• Travel to customer sites up to 70% for on-site engagements.

Skills

Python

SQL

Pre-sale

Customer facing

Architecture

Data integration

Tools

APIs

Cloud platforms

Job description

Location: Mountain View, CA or New York, NY (Office-based)

Duration: Long Term

Client: Direct

Travel: Up to 70% (Customer Sites)

About the Role

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. 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.

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.

Post-sale: Architect and ship in customer-specific production

• 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 elevate 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.