AI Engineer (DLP)

EVERSAFE ACADEMY PTE. LTD.; Singapore; On-site; SGD 120,000 - 180,000; Full time

Job summary

EVERSAFE ACADEMY PTE. LTD. in Singapore seeks an AI Engineer to lead architecture and deployment of autonomous AI agents for safety training analytics. Reporting to the CTO, you will build multi-step agentic workflows that integrate with enterprise data to enable real-time decision-making.

You will design RAG pipelines, enable secure integrations with CRM/LMS, implement HITL workflows and robust governance, and collaborate with Data Engineers to optimize data layers for high-speed retrieval.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, AI, or a related field.
• Minimum 3 years in AI/ML engineering with 1 year in Generative AI production.
• Hands-on with orchestration frameworks like LangGraph, LlamaIndex, or CrewAI.
• Strong Python and asynchronous programming skills; proficient API design.
• Experience with frontier/open-source models and vector stores.
• Familiarity with MCP and A2A patterns; solid ML frameworks experience.

Responsibilities

• Agentic Workflow Orchestration: design and deploy multi-agent systems for autonomous reasoning and task decomposition.
• Advanced RAG Architectures: develop high-precision RAG pipelines with grounding in docs.
• System Integration & Tool Use: integrate LLMs with internal APIs and third-party platforms.
• Model Development & Optimisation: build ML models to complement GenAI features.
• AI Safety & Governance: HITL workflows, prompt guardrails, and PII masking.
• Evaluation & Observability: benchmark and monitor reliability, latency and reasoning.
• Cross-Functional Collaboration: work with Data Engineers to optimise the data layer.

Skills

AI/ML engineering

Generative AI

Python

Asynchronous programming

REST APIs

Model deployment

Cloud platforms

Data integration

Agentic orchestration

LangGraph

LlamaIndex

CrewAI

Education

Bachelor’s or Master’s degree in Computer Science, AI, or a related field

Tools

GPT-5

Claude 4.6

Llama 4

Mistral

Pinecone

Weaviate

Milvus

MCP

A2A

PyTorch

TensorFlow

AWS Bedrock

Azure AI Foundry

Vertex AI

LangSmith

DeepEval

Ragas

Job description

Job Title: AI Engineer

Department: Technology & Digital Transformation

Reports to: Chief Technology Officer (CTO)

(DLP-supported, commensurate with experience)

Position Summary

The AI Engineer will be a cornerstone of Eversafe Academy’s digital transformation under the IMDA Digital Leaders Programme (DLP). Reporting directly to the CTO, you will lead the architecture and deployment of autonomous AI agents designed to revolutionise safety training analytics and operational compliance. This is not a "wrapper" development role; you will build sophisticated, multi-step agentic workflows that integrate deeply with enterprise data layers to drive real-time decision-making.

Key Responsibilities

• Agentic Workflow Orchestration: Design and deploy multi-agent systems capable of autonomous reasoning, task decomposition, and tool use to automate complex business processes.

• Advanced RAG Architectures: Develop and optimize high-precision Retrieval-Augmented Generation (RAG) pipelines, utilising hybrid search and re-ranking to ensure 100% grounding in regulatory and technical documentation.

• System Integration & Tool Use: Architect seamless integrations between LLMs and internal APIs/third-party platforms (WhatsApp, CRM, LMS) using MCP and A2A protocols.

• Model Development & Optimisation: Design and implement traditional Machine Learning models (anomaly detection, classification, and regression) to complement GenAI features.

• AI Safety & Governance: Implement robust "Human-in-the-loop" (HITL) workflows, prompt-injection guardrails, and PII masking to ensure secured and compliant agentic behavior.

• Evaluation & Observability: Establish rigorous benchmarking to evaluate, monitor and improve agent reliability, latency, and reasoning accuracy.

• Cross-Functional Collaboration: Partner with Data Engineers to ensure the underlying data layer is optimised for high-speed retrieval and agentic consumption.

Qualifications & Experience

• Education: Bachelor’s or Master’s degree in Computer Science, AI, or a related field.

• Experience: Minimum of 3 years in AI/Machine Learning Engineering, with at least 1 year of dedicated experience in Generative AI production environments.

• Agentic Expertise: Deep hands-on experience with orchestration frameworks: LangGraph, LlamaIndex, or CrewAI.

• Technical Stack:
  * Models: Experience with frontier models (GPT-5, Claude 4.6) and fine-tuning
  open-source models (Llama 4, Mistral).
  * Vector Infrastructure: Proficiency in Pinecone, Weaviate, or Milvus.
  * Protocols: Familiarity with Model Context Protocol (MCP) and
  Agent-to-Agent (A2A) communication patterns.
  * ML: Experience with frameworks (PyTorch or TensorFlow)

• Evaluation Tools: Proven experience with DeepEval, Ragas, or LangSmith for systematic testing.

• Engineering Excellence:
  * Expert-level Python and experience with asynchronous programming.
  * Strong API design skills (REST/GraphQL).
  * Familiarity with Cloud AI Orchestrators (AWS Bedrock, Azure AI Foundry,
  or Vertex AI).

Mindset

A "production-first" mentality—understanding that an AI demo is easy, but a reliable AI system is hard.