Agentic Artificial Intelligence (AI) Engineer

Job Description

Location: Tukang, Singapore (West)

Only candidates with the legal right to work in Singapore will be considered. Please note that applicants without this eligibility will not be considered.

Why join Rolls-Royce?

At Rolls-Royce we are proud to be a business that has truly helped to shape the modern world and are committed to always being a force for progress; powering, protecting and connecting people everywhere.

By joining Rolls-Royce, you'll have the opportunity to work on world-class solutions, supported by a culture that believes individuality is our greatest strength, and all perspectives, experiences and backgrounds help us innovate and enable our high-performance culture.

Position Summary

The Agentic AI Engineer designs and delivers the agents that power RRPS's AI-driven operations. This role is accountable for applying LLM-first design principles: every agent built here uses the language model as its reasoning core, with tools and APIs as stateless data endpoints. Engineers in this role maintain rigorous audit trails so every autonomous decision is traceable to a named business authority, and they deliver complete working agents — not prototypes — within few weeks.

What you will be doing:

LLM-First Agent Design & Delivery

Design autonomous agents where the LLM performs all reasoning, classification, and routing — no if-else decision logic in agent code.

Implement agent tool interfaces as stateless, deterministic data endpoints; all business logic lives in the model's reasoning layer.

Deliver production-ready agents within 4–6 week cycles, from capability design through staging validation to live deployment.

Apply structured output schemas and constraint enforcement to ensure agents produce auditable, machine-verifiable responses.

Write comprehensive agent test suites covering happy paths, adversarial inputs, and boundary-condition reasoning.

Multi-Agent Orchestration & Graduated Autonomy

Design multi-agent systems where specialist agents collaborate under a coordinating orchestrator, with clearly bounded authority at each layer.

Implement graduated autonomy protocols: move agents from supervised pilot through validated autonomous to fully autonomous deployment, with defined quality gates at each stage.

Enforce the agent's sanctioned authority boundaries at runtime — reject tool calls that exceed what the agent is permitted to do, before execution.

Build agent-to-agent communication patterns that preserve audit context across handoffs, ensuring end-to-end traceability.

Monitor agent behaviour in production; detect drift from approved operating parameters and escalate to human oversight.

Audit, Compliance & Institutional Knowledge

Implement comprehensive audit trails capturing decision rationale, tool calls, inputs, outputs, and the human authority chain behind each action.

Ensure every agent output includes sufficient explanation for regulatory review under EU AI Act transparency obligations.

Document agent design decisions, authority boundary definitions, and known limitations in the CoE knowledge base.

Support internal compliance authorities consultations by providing technical documentation of agent capabilities and human oversight controls.

Contribute to the CoE's institutional knowledge library — patterns, lessons learned, and reusable agent components.

Platform Integration & Quality

Integrate agents with enterprise systems via standard API contracts, event queues, and Model Context Protocol (MCP) tool interfaces.

Implement idempotent agent actions — every autonomous operation must be safe to retry without side effects.

Apply structured validation at all agent output boundaries before downstream system calls.

Participate in CoE code reviews, contributing to shared standards for agent architecture and prompt engineering.

Maintain agent health monitoring: latency, reliability, reasoning quality metrics, and escalation rates.

Position requirements:

LLM-first design: understanding that the model IS the router, classifier, and evaluator — not a call made by deterministic code.

Agent reliability patterns: idempotency, retry safety, graceful degradation without silent fallback.

AI audit and explainability: designing for regulatory review, not just functional correctness.

EU AI Act high-risk system obligations (basic awareness sufficient).

Enterprise integration patterns: event-driven architecture, saga pattern, API gateway, service mesh.

Technical Skills Required

LLM integration: Anthropic Claude, Azure OpenAI or Google Vertex AI — prompt engineering, structured outputs, tool use.

Agent orchestration frameworks: LangChain, AutoGen, CrewAI, LlamaIndex Agents or Semantic Kernel.

Python (primary): async patterns, type annotations, Pydantic data modelling, pytest.

API and event integration: REST APIs, OpenAPI specification, message queues (Azure Service Bus or equivalent).

Workflow orchestration: Prefect, Temporal, Apache Airflow.

Database access via ORM (SQLAlchemy, Django ORM, or Entity Framework Core).

Container deployment: Docker, Kubernetes (AKS or equivalent managed service).

Model Context Protocol (MCP) or equivalent tool interface standards for LLM-to-system integration.

Preferred Qualifications

Degree in Computer Science, Software Engineering, or a related technical discipline

3+ years building production software systems; 1+ year with LLM-integrated or agentic AI applications

Demonstrable experience delivering AI agents or LLM-integrated features in production environments

Experience in regulated industries (financial services, healthcare, industrial operations) preferred

Evidence of technical curiosity — side projects, internal tooling, writing, or community involvement are all relevant

About mtu Power Systems

Power Systems is the Rolls-Royce business which provides world-class power solutions and complete life-cycle support under our product and solution brand mtu. Through digitalization and electrification, we strive to develop drive and power generation solutions that provide answers to the challenges posed by the rapidly growing societal demands for energy and mobility.

We deliver and service comprehensive, powerful and reliable systems, based on both gas and diesel engines, as well as electrified hybrid systems. These technologically advanced solutions serve our customers in the marine and infrastructure sectors worldwide.

Our vision is to ensure that the excellence and ingenuity that shaped our history continues into our future. Our multi-year transformation programme aims to turn Rolls-Royce into a high-performing, competitive, resilient and growing company. Join us, and it can be your future vision too.

Rolls-Royce is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to any protected characteristics.

Relocation assistance is not available for this position.

As part of our selection process, candidates in certain locations may be asked to complete an online assessment, which can include cognitive and behavioural aptitude testing relevant to the role. If required, full instructions for the next steps will be provided.

Job Category

Digital

Posting Date

02 Jul 2026; 00:07