AI Tech Lead (Python, GenAI, MLOps) for our client in Singapore

Optimum Solutions Pte Ltd; Singapore; On-site; SGD 180,000 - 240,000; Full time

Job summary

Optimum Solutions Pte Ltd in Singapore is seeking a senior AI/ML Platform Engineer to lead production AI/ML initiatives and mentor a technical team. You will architect scalable data/AI solutions, implement GenAI capabilities, and collaborate with stakeholders to translate requirements into robust technical outcomes.

You will work with cloud platforms and MLOps tooling, ensuring governance and data privacy while delivering high-impact results in a fast-paced environment.

Qualifications

• Degree in CS/Engineering/Data Science (or related field).
• 8+ years in software or data engineering with 3+ years building AI/ML in production.
• Strong Python skills; Java/Scala a plus; REST APIs and microservices experience.
• Hands-on with ML frameworks: PyTorch, TensorFlow or scikit-learn.
• Experience with LLMs and GenAI tooling (LangChain, LlamaIndex, vector stores, prompt engineering).
• Experience with AWS/Azure/GCP and containers (Docker, Kubernetes).
• Experience with MLOps (MLflow, Kubeflow), CI/CD and monitoring.
• Proven leadership or mentoring of technical teams; strong communication.

Responsibilities

• Lead and mentor data/AI engineering teams.
• Architect and deliver production AI/ML solutions.
• Collaborate with stakeholders to explain complex technical topics.
• Ensure data governance and privacy considerations in solutions.

Skills

Python

REST APIs

Microservices

ML frameworks

GenAI tooling

Cloud platforms

Docker

Kubernetes

MLOps

CI/CD

Monitoring

Team leadership

Communication

GenAI / LLMs

Data governance

Education

Bachelor’s or Master’s degree in CS/Engineering/Data Science

Bachelor’s or Master’s degree in CS/Data Science/Engineering/Statistics

Tools

Spark

Databricks

Snowflake

Kafka

PyTorch

TensorFlow

scikit-learn

LangChain

LlamaIndex

MLflow

Kubeflow

Job description

• Bachelor's or Master's degree in Computer Science, Engineering, Data Science or a related field.
• 8+ years of software or data engineering experience, including 3+ years building and deploying AI/ML solutions in production.
• Strong programming skills in Python (Java or Scala is a plus), and experience with REST APIs and microservices.
• Hands-on experience with ML frameworks such as PyTorch, TensorFlow or scikit-learn.
• Experience with LLMs and GenAI tooling (e.g., LangChain, LlamaIndex, vector stores, prompt engineering, fine-tuning).
• Experience with a major cloud platform (AWS, Azure or GCP) and containers/orchestration (Docker, Kubernetes).
• Experience with MLOps practices and tools (MLflow, Kubeflow or similar), CI/CD and monitoring.
• Proven experience leading or mentoring technical teams.
• Strong communication skills, able to explain technical decisions to non-technical stakeholders.

Preferred Qualifications

• Experience in a regulated industry such as banking or financial services.
• Knowledge of AI governance, model risk management and data privacy regulations (e.g., PDPA, GDPR).
• Experience with data platforms and tools such as Spark, Databricks, Snowflake or Kafka.
• Cloud or AI certifications (e.g., AWS ML Specialty, Azure AI Engineer, GCP ML Engineer).
• Experience with agentic AI, evaluation frameworks and AI security (prompt injection, data leakage).
• Bachelor's or Master's degree in Computer Science, Data Science, Engineering, Statistics or a related field.
• 8+ years of experience in data engineering, analytics or data science, including 3+ years in a lead role.
• Hands-on experience delivering AI/ML solutions in production.
• Strong knowledge of data architecture: data warehouses, lakes or lakehouses, ETL/ELT and streaming.
• Proficiency in Python and SQL, and experience with tools such as Spark, Databricks, Snowflake or similar.
• Experience with a major cloud platform (AWS, Azure or GCP).
• Understanding of data governance, data quality and privacy requirements.
• Strong stakeholder management and communication skills, able to explain complex topics to non-technical audiences.
• Proven ability to lead teams and manage delivery in Agile environments.

Preferred Qualifications

• Experience with GenAI, LLMs and RAG, and with MLOps practices.
• Experience in banking or another regulated industry.
• Knowledge of regulations such as PDPA or GDPR, and of model risk management.
• Relevant cloud, data or AI certifications