AI/ML Engineer

COGNIZANT TECHNOLOGY SOLUTIONS ASIA PACIFIC PTE. LTD.; Singapore; On-site; SGD 120,000 - 180,000; Full time

Job summary

Cognizant Technology Solutions Asia Pacific Pte. Ltd. is seeking an AI/ML Engineer to design, build and deploy production-grade GenAI, RAG, and Agentic AI solutions on Azure.

You will develop end-to-end GenAI pipelines, optimize LLM orchestration, and implement responsible AI and governance while collaborating with data engineering, product, and business teams.

Experience with Azure OpenAI, Azure ML, and vector databases will be highly valued, as will hands-on coding in Python and PySpark.

Qualifications

• Strong programming in Python and PySpark.
• Hands-on experience with LLMs, RAG, Agentic AI, and Generative AI app development.
• Extensive experience with Azure OpenAI Service and the Azure AI ecosystem.
• Experience building end-to-end AI solutions using Azure Machine Learning.
• Knowledge of Prompt Engineering, LLM orchestration, and AI evaluation frameworks.
• Experience with Vector Databases (Azure AI Search, Pinecone, Chroma, Weaviate, etc.).
• Expertise in ML, DL, NLP, and model optimization.
• Experience building scalable data pipelines, feature engineering, and distributed data processing.
• Experience with API development, model deployment, MLOps, monitoring, and CI/CD.
• Strong understanding of Responsible AI, AI Governance, and model explainability.

Responsibilities

• Design, develop, and deploy end-to-end GenAI, RAG, and Agentic AI solutions on Azure.
• Build and optimize LLM orchestration pipelines and AI evaluation frameworks.
• Architect and implement vector search and retrieval systems.
• Develop scalable data pipelines using Python and PySpark.
• Build, train, and optimize ML/DL/NLP models and manage lifecycle with Azure ML.
• Own API development and model deployment with MLOps best practices.
• Implement Responsible AI, governance, and explainability.
• Collaborate with data engineering, product, and business teams to translate requirements into scalable solutions.
• Stay updated with GenAI/Agentic AI frameworks and assess applicability.

Skills

Python

PySpark

LLMs

RAG

Agentic AI

Azure OpenAI Service

Azure Machine Learning

Prompt Engineering

MLOps

CI/CD

Vector Databases

Distributed Data Processing

API Development

Model Deployment

Tools

Azure AI Search

Pinecone

Chroma

Weaviate

LangChain

Databricks

Azure Data Factory

Synapse Analytics

Docker

Kubernetes

Job description

About the Role

We are looking for a AI/ML Engineer with deep, hands-on expertise in designing, building, and deploying production-grade GenerativeAI, RAG, and Agentic AI solutions on the Azure cloud platform. This is a full-stack AI engineering role spanning model development, orchestration, deployment, and operations — ideal for someone who thrives at the intersection of applied machine learning, LLM engineering, and scalable cloud architecture.

You will work on high-impact AI initiatives, building intelligent systems that combine LLMs, retrieval pipelines, and autonomous agents into robust, enterprise-ready applications.

Key Responsibilities

• Design, develop, and deploy end-to-end GenAI, RAG, and Agentic AI solutions using Azure OpenAI Service and the broader Azure AI ecosystem.
• Build and optimize LLM orchestration pipelines, prompt engineering strategies, and AI evaluation frameworks to ensure quality, reliability, and performance.
• Architect and implement vector search and retrieval systems using Azure AI Search, Pinecone, Chroma, Weaviate, or similar technologies.
• Develop scalable, production-grade data pipelines using Python and PySpark, including feature engineering and distributed data processing.
• Build, train, and optimize Machine Learning, Deep Learning, and NLP models, and manage their lifecycle using Azure Machine Learning.
• Own API development and model deployment, applying MLOps best practices including CI/CD, monitoring, and observability.
• Implement Responsible AI, AI Governance, and explainability practices to ensure ethical, transparent, and compliant AI systems.
• Collaborate with cross-functional teams (data engineering, product, and business stakeholders) to translate requirements into scalable AI solutions.
• Stay current with emerging GenAI/Agentic AI frameworks and evaluate their applicability to business use cases.

Must-Have Skills

• Strong programming expertise in Python and PySpark
• Hands-on experience with LLMs, RAG, Agentic AI, and Generative AI application development
• Strong experience with Azure OpenAI Service and the Azure AI ecosystem
• Experience building end-to-end AI solutions using Azure Machine Learning
• Knowledge of Prompt Engineering, LLM orchestration, and AI evaluation frameworks
• Experience with Vector Databases (Azure AI Search, Pinecone, Chroma, Weaviate, etc.)Expertise in Machine Learning, Deep Learning, NLP, and model optimization
• Experience building scalable data pipelines, feature engineering, and distributed data processing
• Experience with API development, model deployment, MLOps, monitoring, and CI/CD
• Strong understanding of Responsible AI, AI Governance, and model explainability

Nice-to-Have Skills

• Experience with AI frameworks such as LangChain, LangGraph, Semantic Kernel, AutoGen, CrewAI
• Hands-on experience with Databricks, Azure Data Factory, Synapse Analytics
• Experience with Docker, Kubernetes, and cloud-native architectures
• Knowledge of multi-agent systems, AI observability, and LLM fine-tuning
• Experience building conversational AI, copilots, and enterprise AI solutions
• Exposure to Financial Services / Capital Markets use cases