Forward Deployed Engineer (Agentic AI)
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Key skills for this role
About the Role
Rimini Street seeks a Forward Deployed Engineer (Agentic AI) to embed with enterprise clients to design, build and operationalize agentic AI solutions in production. The role requires 8+ years of engineering experience and 2+ years shipping AI/ML systems into production.
Key Skills for This Role
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 inside the client's source control, CI/CD and deployment infrastructure
- 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 that 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 engineering, data, security and business stakeholders
- Abstract field learnings into reusable patterns, accelerators and reference architectures
Requirements
- 8+ years of professional engineering experience across production systems
- 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 (incomplete)
Full Job Posting
About Rimini Street
- Rimini Street is a global provider of enterprise software support, managed services and Agentic AI ERP solutions.
- The Company has signed thousands of contracts with Fortune Global 100, Fortune 500, midmarket, public sector and government organizations.
Essential Duties And Responsibilities
- Lead technical discovery, scope agentic AI use cases, and translate business problems into engineering deliverables with measurable success criteria such as cycle time reduction, support deflection, automation rate, security and governance success rate and adoption rate.
- Design target architectures that fit the client's environment, regulatory posture and platform preferences, selecting the right substrate per engagement across hyperscale AI services, ServiceNow and other enterprise AI platforms.
- Write production grade code to deliver the solution, working inside the client's source control, CI/CD and deployment infrastructure, and within 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 that hold under real production variation.
- Implement enterprise safe agent tool execution, including permission scoping, approval gates, audit trails and rollback paths for any agent action that touches systems of record.
- Build evaluation suites that catch 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 run 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, stepping back in when issues exceed the support team's depth or when the system needs architectural intervention.
- Build trusted advisor relationships with client engineering, data, security and business stakeholders, and communicate clearly to both engineering teams and C level audiences.
- Abstract field learnings into reusable patterns, accelerators and reference architectures that feed back into Innovation and shape product direction, methodology and the next engagement.
Experience
- 8+ years of professional engineering experience across production systems, with significant production rather than purely advisory 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 ope (incomplete).
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