Software Engineer, Forward Deployed AI

Ramp Ramp · Fintech · New York, NY · Engineering

Software Engineer on the AI Solutions team at Ramp, a fintech company. This role is deeply client-facing, involving technical discovery, solution design, prototyping, implementation, and production readiness for AI/LLM-based workflows. The engineer partners with AI Solutions Strategists and directly with enterprise customers to translate goals into system requirements, build solutions leveraging core Ramp primitives, and ensure deployed workflows are reliable and adopted.

What you'd actually do

  1. Translate customer goals into clear system requirements and non-functional requirements covering security, privacy, reliability, performance, scalability, and cost.
  2. Partner directly with customers to understand current workflows, constraints, systems, data quality, and adoption blockers.
  3. 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
  4. Prototype and validate workflows with end users to de-risk the approach and prove product-market fit.
  5. Drive projects from bootcamp and technical discovery through implementation, production launch, and operational handoff.

Skills

Required

  • 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.

Nice to have

  • Familiarity with finance operations workflows such as AP, procurement, expenses, close, reconciliation, and reporting.

What the JD emphasized

  • AI Solutions Strategist
  • engineer
  • client-facing
  • system requirements
  • non-functional requirements
  • Evaluation plan
  • core Ramp primitives
  • LLM systems
  • RAG
  • agents
  • monitoring
  • evals

Other signals

  • client-facing
  • production readiness
  • customer engagements
  • LLM systems