Agentic AI Engineer [Python / LangChain / LangGraph]

Luxoft Singapore; Singapore; On-site; SGD 170,000 - 210,000; Full time

Job summary

Luxoft Singapore is seeking AI Engineers to drive a strategic initiative around Agentic AI for Trading Surveillance. You will design, develop, and maintain full-stack Python applications, build RAG systems, and implement robust data pipelines to support AI workloads.

The role requires deep experience in AI/ML solution deployment, data engineering, and cloud-native workflows. You will collaborate across teams to ensure scalable, observable AI systems with strong governance and security

Qualifications

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

Responsibilities

• Design, develop, and maintain full-stack Python apps with modern frontend frameworks.
• Build and optimize Retrieval-Augmented Generation systems for AI apps.
• Create and implement vector databases and knowledge stores.
• Develop APIs connecting frontend interfaces with AI services.
• Implement and maintain CI/CD pipelines for AI apps.
• Monitor performance and troubleshoot issues in production.
• Design and maintain data pipelines and data infrastructure for AI/analytics.

Skills

AI/ML solution implementation

Data Engineering

Full-stack AI integration

LLM fine-tuning

RAG systems design

Data modeling

SQL optimization

ETL/ELT development

Data warehousing

Spark

Kafka

Flink

Snowflake

BigQuery

Redshift

Databricks

Tools

Python

FastAPI

Pydantic

LangChain

LangGraph

Streamlit

Gradio

LLM Monitoring Tools

LangSmith

Arize Phoenix

Spark

Kafka

Flink

Job description

We are looking for AI Engineers for a strategic initiative to build Agentic AI use cases around Trading Surveillance.

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

Mandatory Skills Description:

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

AI & ML Skills:

• Multi-Agent System Design & Orchestration
• Full-stack AI Integration (Frontend to Backend)
• Advanced Prompt Engineering & LLM Fine-tuning
• Agentic Retrieval Augmented Generation (RAG)
• AI Safety, Guardrails & Governance
• Semantic Modeling & Knowledge Graph Construction
• LLM Observability, Evaluation & Monitoring (LLMOps)
• ETL/ELT development and optimization
• Data warehousing & lake architecture (Snowflake, BigQuery, Redshift, Databricks)
• Batch and streaming data processing (Spark, Kafka, Flink)
• Data modeling and schema design
• SQL proficiency and query optimization

Main Technologies:

• Python (FastAPI / Pydantic)
• LangChain & LangGraph
• Streamlit & Gradio (UI/UX for AI)
• LLM Monitoring Tools (LangSmith / Arize Phoenix)