Overview In this role you will help design and operate data and AI-enabled systems at scale in a Boston-based team. You will work with real-time streaming, AI orchestration and cloud-based data pipelines to enable client success. Collaborating with cross-functional teams, you'll shape data-driven solutions and infrastructure, delivering reliable, scalable data services. This opportunity offers exposure to cutting-edge ML tooling and modern DevOps practices in a responsible, adaptable environment.
Compensation / Benefits- remote or hybrid work options
- inclusive, adaptable culture
- growth and learning opportunities
- opportunity to work with AI and cloud technologies
- collaborative cross-functional teams
Responsibilities- Contribute to design and implementation of real-time data pipelines and event-driven architectures
- Work with containerization and cloud-based infrastructure to deploy data and AI workloads
- Collaborate on ML/AI tooling and MLOps practices (MLflow, Kubeflow, SageMaker)
- Utilize IaC tools to provision and manage environments (Terraform, CloudFormation)
- Support data engineering tasks across Python/SQL/Scala stacks and Big Data tech (Spark, Kafka)
- Engage with cross-functional teams to align on architecture, data governance and performance improvements
Key requirements- Experience with real-time streaming and event-driven architectures
- Knowledge of Docker and Kubernetes
- Familiarity with LangChain, OpenAI APIs, or AI orchestration frameworks
- Knowledge of Docker, Kubernetes, and Infrastructure as Code (Terraform, CloudFormation)
- Experience with MLOps tools like MLflow, Kubeflow, or SageMaker
- Experience with Infrastructure as Code (Terraform, CloudFormation)
- Understanding of machine learning data pipelines is a plus
- Relevant cloud or data engineering certifications preferred
- team collaboration
- adaptability
- problem-solving
- Python
- SQL
- Scala
