Senior AI Engineer
Primary stack
Nice to have's
Job description
About the Position
We are looking for a Senior AI Engineer with 6-9 years of experience in AI/ML and 3 years in Data Engineering to join our team in Singapore. You will be part of 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
Requirements
- 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)
- Multi-Cloud AI Infrastructure (AWS Bedrock, Vertex AI, Azure AI, Snowflake Cortex)
- Advanced Prompt Engineering & LLM Fine-tuning
- Agentic Retrieval Augmented Generation (RAG)
- AI Safety, Guardrails & Governance
- Enterprise Application Integration & AI Orchestration
- Semantic Modeling & Knowledge Graph Construction
- High-Scale Vector Database Management
- LLM Observability, Evaluation & Monitoring (LLMOps)
Data Engineering Skills
- Data pipeline design & orchestration (Apache Airflow, Prefect, Dagster)
- 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
- Edio & Render (Deployment & Hosting)
- Streamlit & Gradio (UI/UX for AI)
- OpenAI & Open-Source Models (Llama 3, Mistral)
- Vector Databases (Pinecone, Milvus, Weaviate)
- Cloud Platforms: AWS Bedrock, Google Vertex AI, Azure AI Studio
- LLM Monitoring Tools (LangSmith / Arize Phoenix)
- Data Tools: Apache Spark, Airflow, Kafka, dbt, Snowflake
Nice to Have
- Tesseract OCR
We Offer
- Competitive salary
- Opportunity to work in a dynamic and innovative environment
- Professional growth and development opportunities
About the Company
Luxoft is a global leader in digital transformation and technology services, empowering businesses to thrive in the digital age. Our team is dedicated to delivering cutting-edge solutions and fostering a culture of innovation and excellence.
Apply
If you are passionate about AI and Data Engineering and want to make a significant impact, we encourage you to apply for this exciting opportunity.
© Luxoft DXC. This job description was sourced from the employer's public career page. TheJob is not the employer — we index the posting and route candidates to the source. All content rights and hiring decisions belong to the employer.
Automotive,Finance,Healthcare,Life Sciences,Tech and Telecom
About the Company Luxoft, a DXC Technology Company, is a global digital strategy and software engineering firm with over 17,000 international employees across 58 offices in 29 countries. Headquartered in Zug, Switzerland, Luxoft specializes in providing tailored tech solutions that drive global business transformation. The company focuses on enhancing customer experiences and boosting efficiency through strategy, consulting, and engineering services. Products, Services & Tech Stack Core Solutions: Digital strategy and software engineering services. Technologies & Frameworks: Specific platforms, languages, or tools are not mentioned in the provided text. Project Scope & Target Clients Client Base: Automotive, finance, healthcare, life sciences, tech, and telecom. Engineering Scale: Scope and complexity of engineering projects are not specified in the provided text.
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