Software Engineer, Forward Deployed AI

Ramp - New York, NY (HQ) - original posting ->
Status
Open
Remote policy
Hybrid
Employment type
Full-time
Salary
189,000-330,000 USD / year
Categories
Engineering, Forward Deployed
Source
ramp
First observed
2026-08-18 21:02 UTC
Last seen
2026-08-18 21:02 UTC
Source claims posted
2026-07-28 17:56 UTC
Consecutive misses
0 of 3

What the posting says

About Ramp

Ramp is building the smart infrastructure for finance teams, embedded in the transaction flow of every dollar a business spends. We automate how over $200B in annualized spend flows in and out of 70,000+ companies: authorizing payments, flagging risk, categorizing spend, and closing books.

The problems are high-stakes, data-dense, and unforgiving.

We hire people with high agency and high urgency. We look for slope over intercept. We care less about where you trained and more about what you’ve built. At Ramp, everyone is a builder who owns problems end to end and makes consequential decisions that shape the outcome.

The median Ramp customer saves 5% and grows revenue 16% in their first year – far in excess of businesses operating without Ramp. We believe every ambitious company deserves the same.

If you want to build systems that directly shape how companies move and manage billions, Ramp is the place to do it.

About the Role

As a software engineer on the AI Soltuions team, you will co-lead customer engagements with an AI Solutions Strategist. The Strategist owns business discovery, ROI narrative, stakeholder alignment, and rollout planning. The engineer owns technical discovery, solution design, prototyping, implementation, and production readiness.

This is a deeply client-facing role. You will spend significant time with customers and end users, moving projects from bootcamp and workflow discovery through implementation, launch, and steady production usage.

What You’ll Do

Translate customer goals into clear system requirements and non-functional requirements covering security, privacy, reliability, performance, scalability, and cost.

Partner directly with customers to understand current workflows, constraints, systems, data quality, and adoption blockers.

Create and maintain solution architecture artifacts:

System context and data flow diagrams

Integration plan across Ramp and customer systems

Security model covering permissions, access patterns, and auditability

Evaluation plan covering quality metrics, acceptance tests, and red-teaming

Operational plan covering monitoring, alerting, incident response, and runbooks

Leverage core Ramp primitives to build efficiently, reusing existing product capabilities wherever possible.

Prototype and validate workflows with end users to de-risk the approach and prove product-market fit.

Drive projects from bootcamp and technical discovery through implementation, production launch, and operational handoff.

Ensure deployed workflows are reliable, supportable, measurable, and adopted by customer teams.

Convert deployments into reusable patterns, components, and playbooks for future AI Solutions projects.

What You Need

Experience shipping production software in high-ownership environments.

Ability to work directly with enterprise customers from discovery through production implementation.

Experience in solutions architecture, technical consulting, forward deployed engineering, or pre-sales engineering.

Strong fundamentals in ML/GenAI, including problem decomposition, evaluation, and deployment trade-offs.

Strong coding ability in at least one of: Python, TypeScript/JavaScript, Java, Go, or similar.

Ability to design secure, scalable systems and produce clear technical documentation.

Comfort working across APIs, integrations, data pipelines, customer systems, and cloud infrastructure.

Experience with cloud architecture on AWS, GCP, or Azure, and distributed systems patterns.

Experience building LLM systems, including RAG, agents, monitoring, and evals.

Willingness to travel up to ~75% as needed, flexible based on project needs and client needs

Nice to have: Familiarity with finance operations workflows such as AP, procurement, expenses, close, reconciliation, and reporting.

Benefits available to all full-time Ramp employees (Global)

Flexible PTO

Centralized home-office equipment ordering

Health and wellness stipend

Budget for intra-office travel

Weekly coffee stipend

United States

100% medical, dental & vision insurance coverage for you, with partial coverage for dependents

One Medical annual membership

401(k), including employer match on contributions made while employed by Ramp

Fertility HRA (up to $10,000 per year)

Parental leave: up to 16 weeks (birthing + bonding) or 8 weeks (bonding only) at 100% pay

Pet insurance

In-office perks: lunch, snacks, drinks, and more

Relocation expense coverage to NYC or SF (if needed)

Canada

Group medical, dental, and vision coverage through Sun Life

Life, AD&D, and disability coverage

Fertility drug coverage (up to $4,000 lifetime)

Group Retirement Plan with employer match (RRSP + DPSP)

Parental leave: up to 16 weeks (birthing + bonding) or 8 weeks (bonding only) at 100% pay, with additional time available at reduced pay

Employee Assistance Program and virtual care through Lumino Health

United Kingdom

Private medical insurance through Freedom Elite

Virtual GP and at-home care via eMed x Livi

Workplace pension through Penfold, with salary sacrifice option

Parental leave: up to 16 weeks (birthing + bonding) or 8 weeks (bonding only) at 100% pay with additional time available at reduced pay

Referral Instructions

If you are being referred for the role, please contact that person to apply on your behalf.

Other notices

Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

Beware of recruiting scams: Ramp will only contact you through official @Ramp.com email addresses and will never ask for payment or sensitive personal information during the hiring process.

Ramp Applicant Privacy Notice

Quality

Completeness: 100%

Not enough history yet to judge honesty signals.

Timeline

  1. *
    #163889 2026-08-18 21:02 UTC
    Published