Full Stack Engineer (Python & AI)

TASQ Staffing Solutions; Taguig; On-site; PHP 1,800,000 - 3,500,000; Full time

Job summary

TASQ Staffing Solutions seeks a senior data engineering/AI leader to drive data science initiatives and guide teams in building and deploying advanced data solutions. You will transform raw data into actionable insights and collaborate with business leaders to fuel growth.

The role requires 7–11 years of experience, a Bachelor's degree, and strong full-stack/backend skills including Python, JS frameworks, APIs, microservices, and cloud DevOps, with hands-on AI integration using LLMs and

Qualifications

• Bachelor's degree required.
• 7–11 years of experience.
• Proficiency in English (spoken and written).
• Strong full-stack or backend development skills including Python, Angular/React, RESTful APIs, microservices, SQL/NoSQL, testing, and software architecture.
• Hands-on experience building AI-integrated apps using LLMs, RAG, embeddings, vector databases, and LangChain/LlamaIndex/Autogen.
• Proven cloud and DevOps capability (Azure/AWS/GCP), Docker, Kubernetes, CI/CD, Git, security, reliability, and scalability.

Responsibilities

• Lead data science initiatives to turn raw data into actionable insights.
• Guide teams in development and deployment of ML/AI solutions.
• Utilize statistical modeling and predictive analytics for complex business problems.
• Design and implement data pipelines and data lakes for large-scale processing.
• Oversee creation of data visualizations to communicate insights to stakeholders.
• Manage project timelines and budgets to deliver data-driven solutions on schedule.
• Coach team members to enhance data science and analytics skills.
• Collaborate with business leaders to identify data-driven growth opportunities.
• Promote adoption of innovative data engineering technologies and methodologies.
• Ensure data quality and compliance within analytics frameworks.

Skills

Full-stack development

Python

Angular/React

RESTful APIs

Microservices

SQL/NoSQL databases

Testing

Software architecture

Cloud platforms (Azure/AWS/GCP)

Docker/Kubernetes

CI/CD

Git

LangChain/LlamaIndex/Autogen

Education

Bachelor's degree

Tools

Python

Angular

React

RESTful APIs

Microservices

SQL

NoSQL

Docker

Kubernetes

CI/CD

Git

LangChain

LlamaIndex

Autogen

Azure

AWS

GCP

Job description

• 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

What You Must Have

• 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.

What Sets You Apart

• Preference for at least one of the following fields of study: Artificial Intelligence and Robotics, Business Analytics, Computer and Information Science, Computer Engineering, Computer Programming, Data Processing/Analytics/Science, Engineering, Information Technology, Machine Learning, Management Information Systems, Mathematics, Statistics, Systems Engineering
• Demonstrating proficiency in data science algorithms and workflows
• Utilizing machine learning and deep learning techniques effectively
• Excelling in complex data analysis and predictive modeling
• Managing data pipelines and confirming data quality
• Leveraging programming languages such as Python, R, and MATLAB
• Embracing change and innovation in technology-driven environments