Senior AI Engineer - Agentic AI & Data Infrastructure

Luxoft; Singapore; On-site; SGD 180,000 - 260,000; Full time

Job summary

Luxoft Singapore is seeking AI Engineers to lead a strategic initiative building Agentic AI use cases for Trading Surveillance. You will design, develop, and maintain full-stack Python applications and create robust RAG systems.

You will implement vector stores, APIs, CI/CD pipelines, and data pipelines to support AI and analytics workloads, focusing on performance, observability, and governance. The role demands 6–9 years in AI/ML and 3+ years in data engineering.

Qualifications

• 6 to 9 years of AI/ML solution implementation experience
• Minimum of 3 years of experience in Data Engineering (ETL/ELT, data warehousing, batch/streaming processing)

Responsibilities

• Design, develop, and maintain full-stack Python applications with modern frontend frameworks
• Build and optimize RAG (Retrieval-Augmented Generation) systems for AI applications
• Create and implement efficient vector databases and knowledge stores
• Develop APIs that connect frontend interfaces with backend AI services
• Implement and maintain CI/CD pipelines for AI applications
• Monitor application performance and troubleshoot issues in production
• Design and maintain data pipelines, ETL/ELT workflows, and data infrastructure to support AI and analytics workloads

Skills

AI/ML implementation

Data Engineering

Full-stack AI integration

Prompt engineering

LLM fine-tuning

RAG design

LLMOps

Data modeling

SQL proficiency

Streaming data

Tools

Python

FastAPI

Pydantic

LangChain

LangGraph

Streamlit

Gradio

Spark

Kafka

Job description

Luxoft Singapore is seeking AI Engineers to lead a strategic initiative building Agentic AI use cases for Trading Surveillance. You will design, develop, and maintain full-stack Python applications and create robust RAG systems.

You will implement vector stores, APIs, CI/CD pipelines, and data pipelines to support AI and analytics workloads, focusing on performance, observability, and governance. The role demands 6–9 years in AI/ML and 3+ years in data engineering.