Data Platform / AIOPS Engineer

Job Responsibilities:

• Contributing member of a high performing, agile team focused on generative Artificial Intelligence/ Client in Data & Analytics.
• Assist Data Engineering and Generative AI teams during design and development for highly complex and critical Generative AI projects.
• Responsible for Setup and performance tuning Transformers. RAG production setup/deployments.
• Responsible for setup/maintenance and optimization of language models using PyTorch, Tensorflow, Streamlit and other relevant frameworks.
• Responsible for setup/maintain advanced tools like Semantic Kernel, Langchain, and others for efficient AI model management.
• Code infrastructure and integrate Platform solutions into the data analytic ecosystem.
• Be part of teams delivering all data projects including implementing new data technologies for unstructured, streaming, and high-volume data.
• Developing and deploying distributed computing Big Data applications using frameworks like Apache Spark and Kafka.
• Utilizing programming languages like Java, Spark, Python, with an emphasis in tuning, optimization, and best practices for Data Engineers.
• Leveraging DevOps techniques and practices like Continuous Integration, Continuous
• Deployment, Test Automation, Build Automation and Test-Driven Development to enable the rapid delivery of end user capabilities.
• Developing data solutions on cloud deployments such as AWS
• Industry experience in Financial Services or other regulated industries and compliance and audit practice.
• Hands on experience leading delivery through Agile methodologies
• Management practices by adhering to required standards and processes.
• Works with Architects to design complex solutions and lead from inception to production.
• Creates and maintains DevOps processes, application infrastructure, and utilizes cloud services (including systems, network and other artifacts)
• Reduces technical debt over time with root cause identification and resolution of system problems
• Innovates on and advocates for best practices and improved team processes, mentors junior team members
• Supports live systems to ensure business continuity.

Role Description:

• The Data Platform / AIOPS Engineer will have responsibility for working on a variety of data projects.
• This includes orchestrating pipelines to stage high quality data for consumption by business analysts, data scientists and visualization developers using modern Big Data tools/architectures
• This position requires the candidate to be a team player and results oriented.
• High sense of integrity, good communication skills, great attention to detail and hands on approach with next generation technologies to contribute to a team that delivers the latest streaming & next generation data technologies.

Job Experience Requirements:

• Bachelor's degree in the areas of Computer Science, Engineering, Information Systems, Business, or equivalent field of study required.
• 10+ years of experience as AIOps engineer with strong background in deploying cutting-edge Client/AI platforms.
• Heavy experience using Python (TensorFlow, PyTorch) for production-grade work.
• Commercial experience building Client AI platforms with large datasets.
• Fluent in AWS with IAM (identity and Access Management), elastic containers (ECS), Kubernetes
• History of working on models from concept to production / end-to-end Experience in working with data solutions (Data lakes, cloud data warehouses, i.e., Snowflake or Redshift).
• 5+ years Linux/Unix including basic commands, shell scripting and solution engineering
• 5+ years of experience with S3, AWS Glue, EMR, MKS, RDS, Serverless technologies, DynamoDB, lambda, Kubernetes, Vector databases and graph databases.
• 2+ years of experience supporting Data Pipelines using Matillion/Python/Serverless.
• Experience developing software solutions to build out capabilities on a Big Data and other Enterprise Data Platforms
• Experience with solving problems and delivering high quality results in a fast-paced environment
• AWS SysOps certifications and/or Client/AI Ops related certifications preferred