Senior AI Engineer

NANYANG TECH PTE. LTD.; Singapore; On-site; SGD 180,000 - 280,000; Full time

Job summary

Nanyang Tech PTE. LTD. in Singapore is seeking engineers to design, build, and deploy enterprise AI applications using LLMs, agentic AI, and RAG architectures.

You will create AI-powered workflows, secure integrations with MCP and REST APIs, and implement guardrails and observability across cloud deployments. You will work on production‑quality Python/TypeScript software, leverage Bedrock services, and participate in CI/CD and IaC with GitHub Actions and Terraform.

Qualifications

• Typically requires a minimum of 5 years of related experience with a Bachelor's degree; or 3 years with a Master's degree, or equivalent experience.
• Experience delivering production software, cloud, or AI solutions in an enterprise environment is preferred.

Responsibilities

• Design and develop enterprise Generative AI and Agentic AI applications using LLMs.
• Build AI agents, agent skills/tools, and multi-agent orchestration workflows .
• Design and implement RAG solutions , including document ingestion, embeddings, vector search, hybrid search, and re‑ranking.
• Develop secure integrations with enterprise applications using MCP, REST APIs, and custom functions .
• Develop production-quality software primarily using Python, Typescript and modern software engineering practices.
• Develop AI solutions using Amazon Bedrock, Bedrock AgentCore, OpenSearch, Lambda, API Gateway, and other AWS services .
• Implement AI guardrails, authentication, authorization, identity propagation, and secure access controls .
• Build automated evaluation capabilities for response quality, retrieval accuracy, hallucination, routing, and guardrail effectiveness.
• Implement monitoring and observability for AI applications, including logs, metrics, traces, latency, token usage, and failures.
• Develop and maintain CI/CD and Infrastructure as Code using technologies such as GitHub Actions and Terraform .
• Troubleshoot complex AI, application, integration, authentication, networking, and cloud infrastructure issues.
• Collaborate with engineering, security, product, and business teams to identify and implement AI-driven automation opportunities.
• Document architectures, development standards, operational procedures, and technical solutions.

Skills

Python

TypeScript

LLMs

Agentic AI

RAG architectures

REST APIs

OAuth 2.0

IAM

Education

Bachelor's degree

Master's degree

Tools

Docker

Kubernetes

ECS

EKS

Fargate

Terraform

CloudFormation

GitHub Actions

Job description

Responsibilities

• Design and develop enterprise Generative AI and Agentic AI applications using LLMs.
• Build AI agents, agent skills/tools, and multi-agent orchestration workflows .
• Design and implement RAG solutions , including document ingestion, embeddings, vector search, hybrid search, and re‑ranking.
• Develop secure integrations with enterprise applications using MCP, REST APIs, and custom functions .
• Develop production-quality software primarily using Python, Typescript and modern software engineering practices.
• Develop AI solutions using Amazon Bedrock, Bedrock AgentCore, OpenSearch, Lambda, API Gateway, and other AWS services .
• Implement AI guardrails, authentication, authorization, identity propagation, and secure access controls .
• Build automated evaluation capabilities for response quality, retrieval accuracy, hallucination, routing, and guardrail effectiveness.
• Implement monitoring and observability for AI applications, including logs, metrics, traces, latency, token usage, and failures.
• Develop and maintain CI/CD and Infrastructure as Code using technologies such as GitHub Actions and Terraform .
• Troubleshoot complex AI, application, integration, authentication, networking, and cloud infrastructure issues.
• Collaborate with engineering, security, product, and business teams to identify and implement AI-driven automation opportunities.
• Document architectures, development standards, operational procedures, and technical solutions.

Listed responsibilities are an essential, but not exhaustive, list of the usual duties associated with the position. Changes to individual responsibilities may occur due to business needs.

Requirements

• Strong programming skills, particularly Python , Typescript with good software engineering and coding practices.
• Hands‑on experience building enterprise AI solutions using LLMs, Generative AI, Agentic AI, and RAG architectures .
• Experience developing AI agents, tool/function calling, multi‑agent workflows, and agent orchestration .
• Experience with Amazon Bedrock, Bedrock AgentCore, or equivalent enterprise AI platforms .
• Knowledge of MCP, REST APIs, and enterprise application integration patterns .
• Experience with vector databases/search technologies such as Amazon OpenSearch .
• Understanding of prompt engineering, embeddings, context management, grounding, re‑ranking, and hallucination mitigation.
• Experience implementing AI evaluation, guardrails, responsible AI, and security controls .
• Strong understanding of authentication and authorization technologies including OAuth 2.0, OIDC, JWT, and IAM .
• Experience with AWS or other public cloud platforms.
• Experience with Docker and container platforms such as Kubernetes, ECS, EKS, or Fargate.
• Experience with Infrastructure as Code and automation tools such as Terraform or CloudFormation .
• Experience with CI/CD, Git, and automated testing.
• Strong troubleshooting, problem‑solving, communication, and collaboration skills.
• Ability to quickly learn and apply emerging AI technologies.

Preferred Experience/Skillsets

• Experience building production‑grade enterprise Agentic AI platforms .
• Experience developing MCP servers/clients and agent‑to‑agent integrations .
• Experience integrating AI solutions with enterprise platforms such as ServiceNow, Jira, Confluence, GitHub, or Microsoft 365 .
• Experience with AI observability using CloudWatch, Grafana, OpenTelemetry , or similar technologies.
• Experience with enterprise identity providers such as Okta .
• Experience designing secure AI applications with least‑privilege access, guardrails, auditability, and human‑in‑the‑loop controls .
• Familiarity with AI‑assisted software development tools and workflows.

Education & Experience

Typically requires a minimum of 5 years of related experience with a Bachelor's degree; or 3 years with a Master's degree , or equivalent experience.

Experience delivering production software, cloud, or AI solutions in an enterprise environment is preferred.

Portfolio of past records / projects will be a plus point.