Forward Deployed Engineer (Agentic AI)

Rimini Street

12d•$140,000 - $180,000•Hybrid

About The Position

Rimini Street, Inc. is seeking a Forward Deployed Engineer (Agentic AI) to join their Innovation team. This role involves embedding with enterprise clients remotely, with occasional onsite visits, to design, build, and operationalize agentic AI solutions in production. The engineer will be responsible for creating production outcomes, integrating agentic systems with client platforms and systems of record, and managing the process through cutover, early production, and handover to ongoing support. The role is platform-agnostic and will adapt to the AI platform that best suits the client's needs, including hyperscaler AI services, ServiceNow, and other enterprise AI platforms.

Requirements

Principal-level role requiring engineers with the depth to operate independently inside enterprise client environments and the breadth to span production engineering and applied AI.
8+ years of professional engineering experience across production systems, with significant production time.
2+ years shipping AI or machine learning systems into production, with demonstrated hands-on agentic or LLM-based work.
Proven track record working directly with Fortune 500 or Global 2000 enterprise clients in ambiguous, complex environments.
Track record of operating across the full lifecycle of a system, including architecture ownership, handover to support, and ongoing escalation support.
Demonstrated ability to learn fast and ship in emerging technical disciplines.
Enterprise systems-of-record grounding: hands-on experience with an ERP (SAP, Oracle E-Business Suite, JD Edwards), or strong business-process depth in core enterprise processes.
Production Python and at least one additional enterprise or full-stack language (e.g., TypeScript, Java, Go, C#, Scala).
SQL and data modelling fluency.
Hands-on retrieval-augmented generation experience.
Evaluation suite design for LLM-based systems.
Production observability for AI systems.
Working knowledge of at least one major agentic AI platform (e.g., AWS Bedrock, Azure AI, Google Vertex AI, ServiceNow AI).
Agent tool execution and governance.
Enterprise integration fundamentals (REST, event-driven patterns, identity flows).
UI and front-end fluency in modern web frameworks (e.g., Angular, React).
Durable execution frameworks, event-driven architectures, or workflow orchestration at enterprise scale.
Exceptional written and verbal communication skills.
High autonomy, resilience, and pragmatism in legacy and politically complex environments.
Bachelor’s degree in computer science, engineering, information systems, or related field, or equivalent practical experience.

Nice To Haves

Direct SAP or Oracle E-Business Suite experience preferred.
Experience with multiple agentic AI platforms.
Prior experience as a Forward Deployed Engineer, Applied AI Engineer, or equivalent embedded delivery role at an AI lab, hyperscaler, or systems integrator.
Direct SAP and Oracle EBS experience highly valued for ERP-anchored regional seats.
Consultative and outcomes-driven instincts.
Proactive discipline needed for effective remote embedding.

Responsibilities

Lead technical discovery, scope agentic AI use cases, and translate business problems into engineering deliverables with measurable success criteria.
Design target architectures that fit the client's environment, regulatory posture, and platform preferences.
Write production-grade code to deliver the solution, working within the client's infrastructure and governance processes.
Build and tune retrieval pipelines, prompt architecture, guardrails, agent orchestration, and human-in-the-loop controls.
Implement enterprise-safe agent tool execution, including permission scoping, approval gates, audit trails, and rollback paths.
Build evaluation suites to catch hallucinations, regressions, grounding gaps, and quality drift, and implement production observability.
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 run a structured handover to the ongoing support team.
Act as an escalation backup to the support team after handover.
Build trusted advisor relationships with client stakeholders and communicate clearly to both engineering teams and C-level audiences.
Abstract field learnings into reusable patterns, accelerators, and reference architectures.