Senior Applied AI Engineer

Posted Yesterday
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Singapore, SGP
In-Office
Senior level
Artificial Intelligence • Consulting
The Role
Design, build, evaluate, deploy, and monitor LLM-powered agentic systems for regulatory workflows. Develop LangGraph/LangChain agents, evaluation and observability pipelines, RAG and vector-search systems, and production LLMOps practices. Integrate AI services into Node and React applications while optimizing prompts for cost, latency, and accuracy. Collaborate with product, engineering, and regulatory stakeholders, and mentor colleagues on agent design and evaluation.
Summary Generated by Built In
Our Company

RegASK is the Agentic AI Regulatory Operating System for life sciences and consumer products companies. We believe the future of regulatory work is not just better intelligence; it is intelligent execution.

Powered by vertical AI and backed by a global network of 1,800+ regulatory subject matter experts, RegASK enables organizations to anticipate regulatory change, assess its impact, and orchestrate compliance activities across 160+ markets. Our platform connects regulatory intelligence, decision-making, and workflow execution into a single system designed for modern regulatory teams.

Today, organizations use RegASK across Regulatory Affairs, Quality & Safety, Labeling, Packaging, R&D, and Legal to navigate increasing regulatory complexity with greater speed, confidence, and control. By combining agentic AI, human expertise, and enterprise governance, we are helping global companies transform regulatory operations from a reactive function into a strategic business capability.

As a fast-growing global company, we are always looking for curious, ambitious people who enjoy solving meaningful problems at the intersection of AI, regulation, and enterprise transformation. If that sounds like you, we’d love to meet you.

Position OverviewWe are looking for a Senior Applied AI Engineer to join our AI team, owning the design, evaluation and delivery of LLM-powered agentic systems into the RegASK platform. This role sits at the boundary between AI and product: you will build agent workflows in Python/Typescript and take them all the way into our Node/React platform, working side by side with the product engineering team rather than handling designs over the wall.
You will own outcomes end to end. That means the agent, the evaluation harness that proves it works, and the surface our customers actually touch.
Responsibilities: 
  • Design and implement agent workflows using LangGraph/LangChain, with a strong focus on orchestration, observability and debugging.
  • Build automated evaluation pipelines (factuality, robustness, hallucination detection, guardrails) and use them as the gate for what ships.
  • Optimise embedding models, vector store integrations and RAG pipelines for domain-specific regulatory content.
  • Integrate agentic services into the RegASK platform, working directly in our Node/React codebase alongside product engineering.
  • Maintain prompt pipelines and tune them against cost, latency and accuracy in production.
  • Own deployment, monitoring and continuous improvement of GenAI services (LLMOps), preferably in Azure: ML Studio, Azure OpenAI, Azure AI Foundry.
  • Partner with product, regulatory experts and engineering to translate requirements into agentic pipelines, and mentor colleagues on agent design and evaluation practice.
Requirements:
  • Hands-on production experience with LangGraph, LangChain or comparable agent frameworks.
  • Demonstrated ownership of LLM evaluation and observability: not just building agents, but proving and monitoring their behaviour in production.
  • Strong command of embedding models, vector databases (Pinecone, Weaviate, FAISS, Mongo Atlas Vector Search) and retrieval optimisation.
  • At least one GenAI product surface you built and shipped to real users, end to end.
  • Strong Python engineering background (FastAPI, Transformers, spaCy) and working proficiency in TypeScript with Node and React. You will write both.
  • Experience with SQL and NoSQL data modelling and retrieval.
  • Solid LLMOps/MLOps practice: CI/CD, monitoring, scaling, cost control.
  • Excellent communication skills, able to explain system behaviour and evaluation results to non-technical regulatory and commercial stakeholders.
Good to have:
  • Experience with LLM fine-tuning or adaptation (LoRA, QLoRA, DPO) as a complement to retrieval and prompting.
  • Graph databases or knowledge graphs for hybrid RAG.
  • Continuous evaluation and A/B testing frameworks for agents in production.
  • Background in compliance, life sciences or regulatory intelligence.

What We Offer:
  • Flexible working arrangements (hybrid)
  • Opportunity to work in a high impact role at the intersection on AI, SaaS and Compliance/ Regulatory intelligence
  • Continuous learning and professional development

How to Apply:
If you are excited about this opportunity and believe you have the skills and qualifications to excel as our Senior Applied AI Engineer, please submit your resume for our consideration. 
We appreciate all applications, but only selected candidates will be contacted for an interview.
Thank you for considering joining the RegASK team. We look forward to reviewing your application!

Skills Required

  • Hands-on production experience with LangGraph, LangChain, or comparable agent frameworks
  • Production ownership of LLM evaluation and observability
  • Experience with embedding models, vector databases, and retrieval optimization
  • Built and shipped at least one generative AI product surface to real users end to end
  • Strong Python engineering experience, including FastAPI, Transformers, and spaCy
  • Working proficiency in TypeScript, Node.js, and React
  • Experience with SQL and NoSQL data modeling and retrieval
  • Experience with LLMOps or MLOps, including CI/CD, monitoring, scaling, and cost control
  • Excellent communication skills for explaining system behavior and evaluation results to nontechnical stakeholders
  • Experience with LLM fine-tuning or adaptation using LoRA, QLoRA, or DPO
  • Experience with graph databases or knowledge graphs for hybrid RAG
  • Experience with continuous evaluation and A/B testing frameworks for production agents
  • Background in compliance, life sciences, or regulatory intelligence
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The Company
Singapore
43 Employees
Year Founded: 2017

What We Do

Using artificial intelligence for augmenting regulatory research and ESG issues management. RegASK™’s digital platform routinely monitors, anticipates and reports updates or changes to relevant regulations with instant alerts. Our platform also allows us to zero-in on applicable regulations to identify and analyze any gaps in the compliance of a product. RegASK™ was created by the founders of SPRIM, after more than 17 years of consulting on globalization projects and researching regulatory guidelines for healthcare companies across six of the seven continents. RegASK™ is backed by a team of regulatory experts with a global perspective and years of navigating some of the most complicated regulatory hurdles in markets big and small.

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