AI Engineering Manager
Summary
Leads data science and AI initiatives as an engineering manager — guiding teams that build AI-integrated applications (LLMs, RAG, vector DBs) and data pipelines, and turning data into insights for business decisions. Core stack: Python, Angular/React, cloud (Azure/AWS/GCP), Docker/Kubernetes.
Salary: ₱148,000 – ₱200,000 per month
About the role
Leading data science initiatives to transform raw data into actionable insights for informed decision-making. Guiding teams in the development and deployment of advanced data solutions using machine learning and artificial intelligence.
Key responsibilities
Leading data science initiatives to transform raw data into actionable insights for informed decision-making
Guiding teams in the development and deployment of advanced data solutions using machine learning and artificial intelligence
Utilizing statistical modeling and predictive analytics to address complex business challenges
Designing and implementing data pipelines and data lakes to support large-scale data processing
Overseeing the creation of data visualizations to communicate insights effectively to stakeholders
Managing project timelines and budgets to deliver data-driven solutions on schedule
Coaching team members to enhance their skills in data science and analytics
Collaborating with business leaders to identify opportunities for leveraging data to drive growth
Promoting the adoption of innovative technologies and methodologies in data engineering and analytics
Confirming data quality and compliance within analytics frameworks to maintain integrity
About you
At least a Bachelor's degree
At least 7 to 11 years of experience
Oral and written proficiency in English required
Strong full-stack or backend development skills, including Python, Angular or React, RESTful APIs, microservices, SQL/NoSQL databases, testing, and software architecture
Hands-on experience building AI-integrated applications, using LLMs, RAG, embeddings, vector databases, and frameworks such as LangChain, LlamaIndex, or Autogen
Proven cloud and DevOps capability, including Azure, AWS, or GCP deployment, Docker, Kubernetes, CI/CD, Git, security, reliability, and scalability
Proficiency in data science algorithms and workflows
Utilizing machine learning and deep learning techniques effectively
Excelling in complex data analysis and predictive modeling
Leveraging programming languages such as Python, R, and MATLAB
Skills
- AI
- Analytics
- Angular
- API
- AutoGen
- AWS
- Azure
- CI/CD
- Cloud
- Data Engineering
- Data Lake
- Data Pipelines
- Data Quality
- Data Science
- Deep Learning
- DevOps
- Docker
- Embeddings
- GCP
- Git
- Kubernetes
- LangChain
- LlamaIndex
- LLM
- Machine Learning
- MATLAB
- Microservices
- NoSQL
- Predictive Analytics
- Predictive Modeling
- Python
- React
- REST
- SQL
- Vector Databases