Senior Solution Architect & Data AI

FPT Asia Pacific; Singapore; On-site; SGD 100,000 - 140,000; Full time

Job summary

A leading technology firm is seeking a highly skilled Modern Data & AI professional in Singapore. The candidate will design, build, and present scalable data and AI solutions for clients, supporting digital transformation initiatives. Key responsibilities include engaging with clients for solution design, conducting workshops, and building data pipelines using technologies like Databricks and Spark. The ideal candidate has strong experience in cloud platforms, AI/ML frameworks, and presales activities, driving enterprise governance and scalable solutions.

Qualifications

• Hands-on engineering experience in modern cloud data platforms and AI/ML frameworks.
• Experience delivering end-to-end Data & AI solutions in production.
• Proven presales experience: solution design, demos, POCs, RFP/RFI responses.
• Strong understanding of distributed systems, MLOps, GenAI, and enterprise data governance.
• Ability to communicate with senior stakeholders and translate business problems into scalable technical solutions.

Responsibilities

• Engage with clients to understand business requirements and translate them into technical solutions.
• Conduct solution workshops, technical demos, and POCs showcasing capabilities.
• Support proposal development and commercial discussions with stakeholders.
• Design and implement solutions on Databricks, Snowflake, and Google BigQuery.
• Build robust data pipelines using Spark, Airflow, and Kafka.

Skills

Cloud data platforms

AI/ML frameworks

Data engineering

MLOps

Presales support

Data governance

GenAI ecosystems

Tools

Databricks

Snowflake

Microsoft Fabric

Google BigQuery

Spark

MLflow

AWS SageMaker

Azure ML

Informatica

Microsoft Purview

Kubeflow

Job description

We are seeking a highly skilled Modern Data & AI professional with hands-on experience across cloud data platforms, advanced data engineering, AI/ML frameworks, GenAI ecosystems, and presales activities. The candidate will design, build, and present scalable data and AI solutions to clients, supporting enterprise digital transformation initiatives.

Key Responsibilities

Presales & Solutioning

• Engage with clients to understand business requirements and translate them into technical solutions.

• Conduct solution workshops, technical demos, and POCs showcasing capabilities in Modern Data Platforms, AI/ML, and GenAI.

• Support proposal development, RFP responses, and commercial discussions with stakeholders.

• Provide guidance on architecture, feasibility, and technology adoption strategies.

Modern Data Platforms

• Design and implement solutions on Databricks, Snowflake, Cloudera CDP, Microsoft Fabric, and Google BigQuery.

• Develop Lakehouse and distributed data systems with high performance and reliability.

Data Engineering

• Build robust data pipelines using Spark, Airflow, Delta Lake, Kafka, and DBT.

• Ensure data quality, observability, and reliability in production workflows.

Data Governance & Catalog

• Implement enterprise governance frameworks leveraging Informatica, Microsoft Purview, Collibra, Unity Catalog, and Alation.

• Establish policies for metadata management, lineage, data quality, and compliance.

MLOps & AI Engineering

• Operationalize ML pipelines using MLflow, Kubeflow, Amazon SageMaker, and Azure ML.

• Automate model training, deployment, registry, and monitoring within scalable CI/CD workflows.

ML & AI Algorithms

• Develop AI models including Neural Networks, Classical ML algorithms, Transformers, NLP, Computer Vision, and Recommendation Systems.

• Optimize model performance for enterprise-grade use cases.

GenAI Platforms

• Build solutions using Azure OpenAI / Foundry, AWS Bedrock, and Vertex AI.

• Implement prompt engineering, fine-tuning, RAG pipelines, and AI agent workflows.

Agentic AI Development

• Design autonomous agent systems using LangChain, CrewAI, AutoGen, LlamaIndex, MCP, and A2A.

• Integrate multi-agent orchestration and tool calling capabilities for enterprise automation.

RAG & Vector Database Development

• Implement Retrieval-Augmented Generation (RAG) systems using Pinecone, Weaviate, Redis Vector, and Milvus.

• Build semantic search, embedding pipelines, and vector store integrations.

Data Architecture

• Define and implement enterprise architectures such as Data Mesh, Data Fabric, and Lakehouse.

• Drive architectural governance, best practices, and capability roadmaps.

Industry Use Cases

• Deliver solutions for Fraud Detection, Customer 360, Document AI, Predictive Analytics, and other industry-specific AI initiatives.

Requirements

• Hands-on engineering experience in modern cloud data platforms and AI/ML frameworks.

• Experience delivering end-to-end Data & AI solutions in production.

• Proven presales experience: solution design, demos, POCs, RFP/RFI responses.

• Strong understanding of distributed systems, MLOps, GenAI, and enterprise data governance.

• Ability to communicate with senior stakeholders and translate business problems into scalable technical solutions.