Job Description

We are seeking a Junior Solution Architect with a strong foundation in data science , MLOps , cloud data platforms , and modern data engineering to help design and implement real-time data integration and AI-enabled architectures. Working alongside experienced Solution Architects and Engineering teams, this role provides an opportunity for an early-career professional to gain hands-on experience designing scalable streaming data solutions that power enterprise AI, cloud modernization, and real-time analytics.

The ideal candidate is eager to apply data science and machine learning concepts to real-world enterprise challenges, expand technical expertise across modern cloud and data technologies, and develop into a trusted technical architect within a collaborative, fast-paced environment.

Responsibilities

• Design and implement scalable real-time data integration and Change Data Capture (CDC) solutions using the Striim platform.
• Design streaming data architectures connecting enterprise databases, cloud data platforms, messaging systems, and AI/ML environments.
• Develop data pipelines that support machine learning workflows, feature engineering, model inference, and real-time AI applications.
• Build proof-of-concepts, reference architectures, and deployment patterns for enterprise implementations.
• Configure, optimize, and troubleshoot data pipelines across cloud and hybrid environments.
• Collaborate with Engineering, Product, and GTM Engineering teams to validate architectural designs, resolve complex technical challenges, and improve platform capabilities.
• Participate in architecture reviews, implementation planning, and production readiness activities.
• Create technical documentation, architecture diagrams, and implementation best practices.
• Evaluate emerging technologies across AI , MLOps , cloud computing , and real-time data streaming.

Requirements

• 1–3 years of professional experience or equivalent graduate research, internships, or project experience in data science , machine learning , data engineering , cloud engineering , or solution architecture.
• Strong foundation in data science , including machine learning algorithms , model selection, feature engineering, and the machine learning lifecycle.
• Understanding of modern MLOps practices, including model deployment, inference, monitoring, versioning, and CI/CD for machine learning applications.
• Experience or academic exposure to machine learning frameworks and platforms such as MLflow , Kubeflow , Vertex AI , SageMaker , or Azure Machine Learning .
• Familiarity with modern data integration concepts, including Change Data Capture (CDC) , event-driven architectures, and real-time streaming data pipelines.
• Working knowledge of relational and NoSQL databases , including SQL proficiency and database administration fundamentals.
• Experience with cloud platforms and modern cloud data ecosystems, including AWS , Azure , GCP , Databricks , Snowflake , BigQuery , Amazon Redshift , or Azure Synapse .
• Experience programming in Python or Java and working with REST APIs and JSON .
• Understanding of Docker containers and modern DevOps concepts; familiarity with Kubernetes , Git , and CI/CD pipelines .
• Strong analytical, troubleshooting, written, and verbal communication skills.
• Demonstrated curiosity, adaptability, and a passion for learning emerging technologies in AI , cloud computing , and real-time data streaming.
• Bachelor's or Master's degree in Computer Science , Data Science , Software Engineering , Information Systems , or a related technical discipline.

Benefits

• Competitive salary and pre-IPO stock options
• Comprehensive health care plans (medical, dental and vision), including medical and dependent FSA
• Paid Time Off (Vacation, Sick & Public Holidays)
• The chance to contribute to and shape an upbeat, fully engaged culture

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