Forward Deployed AI Engineer

About the role

RE:AI is Singtel Digital InfraCo's sovereign AI platform, offering GPU-as-a-Service on NVIDIA infrastructure, a Model-as-a-Service catalog and a Token-as-a-Service gateway, running in Singtel's sovereign data centres. It is building a customer-facing AI engineering function inside Customer Success that turns AI conversations into signed pilots. The engineer works with prospective and existing customers from the first meeting through to a live pilot, doing roughly half technical work and half commercial reasoning.

Key responsibilities

• Work with Customer Success and Sales to understand a customer's problem and constraints, then decide what to build to move the deal forward.
• Build prototypes, custom demos and reference deployments on RE:AI (agentic workflows, retrieval, tool use, guardrails) and demonstrate them live.
• Size the platform: GPU sizing, architecture, inference benchmarking and model selection against latency, throughput and cost targets.
• Support the pilot: integration guidance, tuning and acting as the escalation point until the AI infrastructure and production team takes over.
• Turn patterns across customers into reusable demos, templates or accelerators.
• Represent the platform to customer engineers, architects and CXOs, explaining trade-offs in their language.
• Write technical content for RFPs, tenders and compliance responses, and support bid and commercial teams.
• Model TCO, token economics and commercial structuring, and contribute to reference architectures, write-ups, webinars and internal enablement.

Required profile

• Genuinely customer-facing: able to run technical conversations with customer engineers, hold your ground and read the room.
• Hands-on AI experience: has personally built with LLMs and agents (tool calling, retrieval, orchestration, prompting, evaluation).
• Excellent spoken and written communication, able to present to mixed audiences and write proposals and tender responses.
• Commercial sense: can build or reason about TCO models and explain why a customer should choose this solution.
• Comfortable with ambiguity, defining your own scope and travelling or working on site when needed.

Required skills

• Sound engineering fundamentals: strong in at least one backend stack, comfortable with APIs and cloud basics, able to reason about model behaviour in production.
• Nice to have: product management or product owner experience; full-stack prototyping; enterprise RFP or public sector tender experience; TCO and commercial modelling.
• Nice to have: familiarity with GPU infrastructure, inference serving, benchmarking, LLM gateways, guardrails or model-serving platforms; regulated industry experience.