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Rimini Street

Provides third-party enterprise software support

Forward Deployed Engineer - Agentic AI

AI Application EngineeringConfirmed live in the last 24 hours
Full-timeTokyo, JapanNo salary listed

About the Job

Requirements

  • At least 8 years of professional engineering experience across production systems, including significant production work rather than purely advisory work.
  • At least 2 years of experience shipping AI or machine learning systems into production, with hands-on agentic or large language model-based work.
  • A track record working directly with Fortune 500 or Global 2000 enterprise clients in ambiguous, complex environments.
  • Experience operating across a system's full lifecycle, including architecture ownership, handover to support, and ongoing escalation support.
  • The ability to learn and deliver in emerging technical disciplines; recent agentic AI work learned quickly on the basis of strong fundamentals is acceptable.
  • Hands-on experience with a supported enterprise resource planning system (SAP, Oracle E-Business Suite, or JD Edwards), or strong business-process knowledge in procurement, finance, or order-to-cash. This is required for ERP-anchored regional seats.
  • Experience with enterprise resource planning and systems of record such as SAP, Oracle E-Business Suite, JD Edwards, Infor, ServiceNow, Salesforce, or Workday. This is required for ERP-anchored regional seats.
  • Experience with multiple agentic artificial intelligence platforms and the ability to deliver on the platform a client has standardized on.
  • Production Python and at least one additional enterprise or full-stack language such as TypeScript, Java, Go, C#, or Scala, including modern agent frameworks and patterns.
  • SQL and data modeling fluency, including reasoning about enterprise data quality, lineage, permissions, and operational semantics.
  • Hands-on retrieval-augmented generation, including chunking, embeddings, vector stores, and reranking.
  • Ability to design evaluation suites for large language model-based systems, including regression detection, hallucination measurement, and grounding checks.
  • Experience instrumenting production observability for artificial intelligence systems, including latency, token usage, error rate, and output drift.
  • Working knowledge of at least one major agentic artificial intelligence platform, such as AWS Bedrock, Azure AI, Google Vertex AI, or ServiceNow AI, and willingness to learn others as engagements demand.
  • Knowledge of agent tool execution and governance, including the Model Context Protocol or equivalent tool interfaces, permission scoping, scoped credentials, approval gates, audit trails, and safe execution controls.
  • Knowledge of enterprise integration fundamentals, including REST and event-driven patterns, identity flows such as OpenID Connect and Security Assertion Markup Language, and secure deployment into client-controlled environments.
  • User interface and front-end fluency in modern web frameworks such as Angular or React, sufficient to build or extend the user-facing layer of agentic solutions.
  • Exceptional written and verbal communication across technical and executive audiences, consultative and outcomes-driven instincts, autonomy, resilience, pragmatism in legacy and politically complex environments, and the discipline needed for effective remote embedding.
  • A bachelor's degree in computer science, engineering, or information systems, or equivalent practical experience.

Responsibilities

  • Lead technical discovery, scope agentic AI use cases, and translate business problems into engineering deliverables with measurable success criteria, including cycle-time reduction, support deflection, automation rate, security and governance success rate, and adoption rate.
  • Design target architectures that fit each client's environment, regulatory posture, and platform preferences, selecting the appropriate substrate across hyperscaler AI services, ServiceNow, and other enterprise AI platforms.
  • Write production-grade code within the client's source control, continuous integration and continuous deployment, and deployment infrastructure, following enterprise release governance including change approvals, separation of duties, audit evidence, and rollback planning.
  • Build and tune retrieval pipelines, prompt architecture, guardrails, agent orchestration, and human-in-the-loop controls for real production variation.
  • Implement enterprise-safe agent tool execution, including permission scoping, approval gates, audit trails, and rollback paths for actions that touch systems of record.
  • Build evaluation suites to detect hallucinations, regressions, grounding gaps, and quality drift, and implement production observability for latency, token usage, error rates, accuracy, and output drift.
  • Integrate solutions with client identity, secrets management, network controls, incident response, and compliance tooling.
  • Stay engaged through cutover and the first production iteration cycle, then conduct a structured handover to the ongoing support team, including documentation, runbooks, and knowledge transfer.
  • Act as an escalation backup to the support team after handover, intervening when issues exceed the team's depth or require architectural intervention.
  • Build trusted advisor relationships with client engineering, data, security, and business stakeholders, and communicate with engineering teams and C-level audiences.
  • Abstract field learnings into reusable patterns, accelerators, and reference architectures that inform Innovation, product direction, methodology, and future engagements.

Desired Qualifications

  • Direct SAP or Oracle E-Business Suite experience is preferred.
  • Experience as a Forward Deployed Engineer, Applied AI Engineer, or equivalent embedded delivery role at an AI lab, hyperscaler, or systems integrator.
  • Strong backend engineering experience with recent agentic AI delivery or applied AI research with production deployment exposure.
  • Experience with durable execution frameworks, event-driven architectures, or workflow orchestration at enterprise scale.

About the Company

Rimini Street

Provides third-party enterprise software support

Rimini Street provides third-party support and services for enterprise software from vendors like Oracle, SAP, VMware, Microsoft, and Salesforce, using subscription-based contracts. Its Rimini ONE offering can outsource the entire management of a company’s software stack, including customization support, at approximately half the vendor fees. The company differentiates itself with faster, more cost-effective service and a broad coverage that extends beyond basic maintenance to licensing advice and optimization. The goal is to help organizations extend the life of their existing software, reduce IT spend, and improve overall efficiency across mixed technology environments.

Company size
1,001-5,000
Company stage
IPO
Headquarters
Las Vegas, NV
Founded
2005

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