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Information & Communication Technology 🏢 Full Time ⭐️ Terverifikasi

Senior AI & Healthcare Data Engineer (Work From Home)

BruntWork
Metro Manila
Estimasi Gaji
PHP 90.000 – PHP 160.000
Live Update
15 Mei 2026
Batas Akhir
15 Mei 2027

Deskripsi Pekerjaan

<p>Are you a pioneering Senior AI & Healthcare Data Engineer passionate about transforming healthcare through cutting-edge artificial intelligence? BruntWork is seeking an exceptional talent to join our innovative team in a permanent Work From Home (WFH) capacity. This is a unique opportunity to design, build, and optimize robust AI data pipelines that will power next-generation healthcare solutions.</p><p>As a Senior AI & Healthcare Data Engineer, you will be at the forefront of leveraging large language models (LLMs) and Retrieval-Augmented Generation (RAG) techniques to extract insights and enable intelligent applications from complex healthcare datasets. You'll work with diverse data sources, ensuring data quality, security, and accessibility for our data scientists and machine learning engineers.</p><p>We are looking for someone with a proven track record of 5+ years in data engineering, particularly within the AI and healthcare domains, strong proficiency in Python and SQL, and hands-on experience with LLM/RAG architectures. If you thrive in a remote-first environment, are eager to tackle challenging problems, and are committed to making a real impact on healthcare, we want to hear from you. Enjoy the flexibility of permanent WFH along with comprehensive health perks and a collaborative culture focused on innovation. Join BruntWork and help us shape the future of healthcare AI!</p>

Tanggung Jawab

  • &lt;ul&gt;&lt;li&gt;Design, develop, and maintain scalable and robust AI data pipelines for processing large volumes of healthcare data.&lt;/li&gt;&lt;li&gt;Implement and optimize data ingestion, transformation, and storage solutions using Python, SQL, and other relevant technologies.&lt;/li&gt;&lt;li&gt;Architect and build data infrastructure to support Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) applications.&lt;/li&gt;&lt;li&gt;Ensure data quality, integrity, and security across all data pipelines, adhering to healthcare compliance standards (e.g., HIPAA).&lt;/li&gt;&lt;li&gt;Collaborate closely with data scientists, machine learning engineers, and product teams to understand data requirements and deliver effective solutions.&lt;/li&gt;&lt;li&gt;Monitor pipeline performance, troubleshoot issues, and implement optimizations for efficiency and cost-effectiveness.&lt;/li&gt;&lt;li&gt;Evaluate and integrate new data technologies and tools to enhance our AI and data engineering capabilities.&lt;/li&gt;&lt;li&gt;Mentor junior engineers and contribute to best practices in data engineering and MLOps.&lt;/li&gt;&lt;/ul&gt;

Kualifikasi

  • &lt;ul&gt;&lt;li&gt;Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or a related quantitative field.&lt;/li&gt;&lt;li&gt;Minimum of 5 years of professional experience in data engineering, with a significant focus on AI/ML data pipelines and healthcare data.&lt;/li&gt;&lt;li&gt;Expert-level proficiency in Python and SQL for data manipulation, scripting, and database interaction.&lt;/li&gt;&lt;li&gt;Demonstrable experience with LLM (Large Language Models) and RAG (Retrieval-Augmented Generation) architectures and frameworks.&lt;/li&gt;&lt;li&gt;Hands-on experience with cloud platforms (AWS, Azure, or GCP) and their data services (e.g., S3, BigQuery, Snowflake, Databricks).&lt;/li&gt;&lt;li&gt;Strong understanding of data warehousing, ETL/ELT processes, and big data technologies.&lt;/li&gt;&lt;li&gt;Familiarity with healthcare data standards, terminologies, and regulations (e.g., HL7, FHIR, HIPAA) is highly preferred.&lt;/li&gt;&lt;li&gt;Excellent problem-solving skills, attention to detail, and ability to work independently in a remote environment.&lt;/li&gt;&lt;/ul&gt;

Keahlian yang Dibutuhkan

Python SQL LLM RAG Data Engineering Healthcare Data AI Machine Learning Cloud Platforms Data Pipelines ETL Data Warehousing API Integration Big Data MLOps NLP Distributed Systems

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