Junior Solutions Architect – MLOps, Real-Time Data Integration

Strimi

Junior Solutions Architect designing scalable real-time data integration solutions for cloud data platforms. Collaborating with engineers to enhance AI architectures in a fast-paced environment.

Posted 7/24/2026full-timeRemote • 🇺🇸 United StatesJunior💰 $120,000 - $130,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and implementing scalable real-time data integration solutions, with a strong foundation in data science and machine learning practices. Proficient in cloud platforms and modern data ecosystems, capable of optimizing data pipelines and collaborating effectively across teams.

Highest-signal resume keywords

Data Integration SolutionsMachine Learning AlgorithmsCloud PlatformsChange Data Capture (CDC)Data Pipeline Development

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Applicant Tracking System Keywords

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Hard Skills

Data ScienceMachine LearningFeature EngineeringSQL ProficiencyPython ProgrammingJava ProgrammingREST APIsDockerCI/CDDatabase Administration

Soft Skills

Analytical SkillsTroubleshootingWritten CommunicationVerbal CommunicationAdaptability

Tools & Technologies

StriimMLflowKubeflowVertex AISageMakerAzure Machine LearningAWSAzureGCPDatabricks

Industry Keywords

MLOpsReal-Time Data StreamingEvent-Driven ArchitecturesNoSQL DatabasesCloud Data Ecosystems

Tech Stack

Tools & technologies

Amazon RedshiftAWSAzureBigQueryCloudDockerGoogle Cloud PlatformJavaKubernetesNoSQLPythonSQL

About the role

Key responsibilities & impact

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

What you’ll need

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

Comp & perks

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