Were seeking an experienced and skilled Data and AI Infra Engineer to join our Data Infrastructure team and drive the companys data capabilities at scale.
As the company is fast growing, the mission of the data and AI infrastructure team is to ensure the company can manage data at scale efficiently and seamlessly through robust and reliable data infrastructure.
A day in the life and how youll make an impact:
As a Senior Engineer, you are required to independently lead the design, development, and optimization of our data infrastructure, collaborating closely with software engineers, data scientists, data engineers, and other key stakeholders. You are expected to own critical initiatives, influence architectural decisions, and mentor engineers to foster a high-performing team
You will:
Lead the design and development of scalable, reliable, and secure data storage, processing, and access systems.
Define and drive best practices for CI/CD processes, ensuring seamless deployment and automation of data services.
Oversee and optimize our machine learning platform for training, releasing, serving, and monitoring models in production.
Own and develop the company-wide LLM infrastructure, enabling teams to efficiently build and deploy projects leveraging LLM capabilities.
Own the company's feature store, ensuring high-quality, reusable, and consistent features for ML and analytics use cases.
Architect and implement real-time event processing and data enrichment solutions, empowering teams with high-quality, real-time insights.
Partner with cross-functional teams to integrate data and machine learning models into products and services.
Ensure that our data systems are compliant with the data governance requirements of our customers and industry best practices.
Mentor and guide engineers, fostering a culture of innovation, knowledge sharing, and continuous improvement.
Requirements: 7+ years of experience in data infra or backend engineering.
Strong knowledge of data services architecture, and ML Ops.
Experience with cloud-based data infrastructure in the cloud, such as AWS, GCP, or Azure.
Deep experience with SQL and NoSQL databases.
Experience with Data Warehouse technologies such as Snowflake and Databricks.
Proficiency in backend programming languages like Python, NodeJS, or an equivalent.
Proven leadership experience, including mentoring engineers and driving technical initiatives.
Strong communication, collaboration, and stakeholder management skills.
Bonus Points:
Experience leading teams working with serverless technologies like AWS Lambda.
Hands-on experience with TypeScript in backend environments.
Familiarity with Large Language Models (LLMs) and AI infrastructure.
Experience building infrastructure for Data Science and Machine Learning.
Experience collaborating with BI developers and analysts to drive business value.
Expertise in administering and managing Databricks clusters.
Experience with streaming technologies such as Amazon Kinesis and Apache Kafka.
This position is open to all candidates.