Forward Deployed Engineer (Agentic AI)

Overview

Position Summary

Forward Deployed Engineer (Agentic AI)

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

• This is a Principal-level role.
• We are looking for engineers with the depth to operate independently inside enterprise client environments, the breadth to span production engineering and applied AI, and the demonstrated ability to ship in a discipline that is still being defined.
• We weight recent, hands-on agentic AI work heavily, recognizing that production agentic systems are a young discipline.
• Equivalent experience from adjacent disciplines, including machine learning engineering, applied AI research with production deployment exposure, or senior backend engineering with recent agentic shipping, is welcomed.
• 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 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. Candidates whose recent agentic AI work was learned quickly on the back of strong fundamentals are explicitly in scope.
• Education
• Bachelor s degree in computer science, engineering, information systems or related field, or equivalent practical experience.

Location

• and Travel
• Remote UAE
• Travel typically 25 percent to work with clients, prospects, partners or attend events.