Senior Data Engineer (AI)

TL;DR

Senior Data Engineer (AI/AWS): Building and maintaining scalable data pipelines and generative AI workflows for workforce management solutions with an accent on integrating LLMs and AWS infrastructure. Focus on automating the ML lifecycle, designing real-time streaming pipelines, and developing production-grade AI-driven features.

Location: Australia

Company

hirify.global is a global innovation powerhouse and market leader in AI, cloud, and digital software, serving over 25,000 businesses worldwide.

What you will do

• Partner with ML engineers and data scientists to translate business needs into production features for WFM tools.
• Build and maintain scalable data pipelines to prepare data for feature consumption.
• Design and implement generative AI workflows, integrating Amazon Bedrock and foundation models into agentic features.
• Automate the ML/AI lifecycle, including data preparation, model training, inference, deployment, and monitoring.
• Collaborate cross-functionally to develop APIs and UX that bring AI features to life.
• Apply AI-assisted engineering practices using tools like GitHub Copilot and Claude Code.

Requirements

• 5+ years of experience as a Data Engineer building and deploying solutions on AWS.
• Proficiency in Python and JavaScript for maintaining high-quality, production-grade code.
• Hands-on experience with AWS services: Lambda, S3, Glue, Athena, Kinesis, EC2/ECS, RDS, and DynamoDB.
• Strong knowledge of SQL, data warehousing, ETL, and Data Lake concepts.
• Experience building real-time, low-latency data streaming pipelines and working with NoSQL stores (e.g., MongoDB).
• Experience with GitHub, CI/CD, containerized deployment, and microservice architecture.

hirify.global-to-have">hirify.global to have

• Experience with Apache Spark, AWS Step Functions, and Snowflake.
• Knowledge of agentic AI workflows or orchestration frameworks.
• Experience with Amazon Bedrock or other generative AI/LLM platforms.
• Familiarity with Kubernetes, IAM roles, and security groups within AWS.
• Experience productionizing machine learning models.

Culture & Benefits

• Opportunity to drive innovation at both the application and infrastructure levels.
• Work within a fast-paced, collaborative environment with high standards of execution.
• Access to cutting-edge AI tools and technologies.
• Inclusive workplace committed to equal opportunity regardless of background or neurotype.