Applied AI Engineer

PebbleRoad is a leading Singapore-based AI services company dedicated to orchestrating intelligent, end-to-end business workflows for large organizations across financial services, government, healthcare, and more. With over 20 years of experience, we move organizations past operational bottlenecks by building AI-native processes that transform complex, unstructured documents into reliable business data. Our approach, centered around services, solutions, and products like DocuPrism, delivers dramatic improvements in efficiency, governance, and speed across core business operations.

We are now strategically expanding our team to scale our AI services and accelerate the development of our innovative AI products pipeline. Join us in shaping the future of intelligent automation.

The role

We are looking for an Applied AI Engineer to build practical AI capabilities for our product. The role focuses on the AI layer: designing AI workflows, selecting suitable models, evaluating output quality, and exposing AI features through APIs for our backend and frontend developers to consume.

You will work closely with product managers, backend engineers, and frontend engineers to turn business problems into reliable AI-powered features.

What you’ll do

• Design and develop AI services for real product use cases

• Build APIs for AI capabilities so they can be integrated into existing systems

• Develop OCR and document intelligence solutions with varying layouts

• Use LLMs for tasks such as rewriting, summarisation, classification, and recommendation

• Build recommendation logic based on user needs, pain points, and browsing behaviour

• Evaluate AI outputs for accuracy, relevance, consistency, and reliability

• Create fallback logic, confidence scoring, and guardrails for uncertain AI outputs

• Monitor AI performance and improve models or prompts over time

What we’re looking for

• Strong experience in AWS stacks

• Experience working with LLMs, prompt engineering, structured outputs, and AI APIs

• Experience with OCR/document AI, especially extracting data from invoices, receipts, or forms

• Understanding of recommendation systems, ranking logic, embeddings, or similarity matching

• Experience with structured data and basic data processing

• Ability to evaluate AI quality using test cases, benchmarks, and error analysis

• Basic understanding of cloud deployment, logging, and production reliability

• Experience with vector databases, RAG, LangChain, LlamaIndex, or Hugging Face

• Knowledge of MLOps, CI/CD, Docker, or model monitoring

• Experience building AI features that have gone beyond proof-of-concept into production

Benefits

• Competitive compensation with performance-based bonuses

• Medical insurance

• Remote-first work environment

• Opportunity to work on real, enterprise-grade AI systems—not demos

• Access to training and learning resources to deepen expertise in ML systems and infrastructure