Senior Software Engineer

Voyantis

. Design and build production-grade systems across the Engage stack, including cloud data pipelines, ML and decisioning services, backend services, and customer-facing UI .

Posted 11/9/2026full-timeRemote • IsraelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and building production-grade cloud systems, with a strong focus on data pipelines, machine learning integration, and backend services. Proficient in Python and familiar with cloud-native architectures, ensuring systems are scalable and continuously learning.

Highest-signal resume keywords

Cloud Systems ArchitectureMachine Learning IntegrationPython ProficiencyEvent-Driven ArchitecturesData Pipeline Tooling

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Cloud SystemsSoftware Design PrinciplesData StructuresConcurrencyPythonAWS LambdaSnowflakeAirflowDockerKubernetes

Soft Skills

Excellent CommunicationIndependent LearningCuriosityOwnershipAccountability

Tools & Technologies

DbtSparkGlueArgoCDPulumiTerraform

Certifications & Qualifications

BSc in Computer ScienceBSc in Engineering

Industry Keywords

Production SystemsData PipelinesMachine LearningCloud-NativeEvent-Driven Architecture

Tech Stack

Tools & technologies

AirflowAWSBigQueryCloudDockerJavaKubernetesNode.jsPythonScalaSnowflakeSparkTerraformTypeScriptGo

About the role

Key responsibilities & impact

Design and build production-grade systems across the Engage stack, including cloud data pipelines, ML and decisioning services, backend services, and customer-facing UI
Build closed-loop systems that turn ML predictions into automated decisions delivered to customers' databases and CRM systems
Feed outcomes back into systems so they continuously learn
Take features from idea through architecture, development, production deployment, monitoring, and iteration
Collaborate with the engineering lead, VP Product, and senior data scientists to productionize and scale models and research
Monitor performance and prioritize work using data-driven decisions
Participate in code reviews and uphold engineering standards and best practices

Requirements

What you’ll need

5+ years of hands-on experience building large-scale, production cloud systems end-to-end
Experience with architecture design, development, testing, and operating systems in production
Strong understanding of software design principles, concurrency, data structures, and cost/performance trade-offs
Experience with cloud-native, event-driven architectures such as AWS Lambda, batch, SQS, and S3, or equivalents
Experience with modern data warehouses such as Snowflake, BigQuery, or Databricks
Experience with pipeline tooling such as dbt, Airflow, Spark, or Glue
Comfortable working across data pipelines, backend/applicative services, ML/algorithmic code, and frontend/UI
Proficiency in Python or a similar general-purpose language such as Go, Java, Scala, C#, or TypeScript/Node
Adaptability to learn Python quickly
Strong sense of ownership and accountability for systems end-to-end
Excellent communication skills, independent-learning ability, and curiosity
BSc in Computer Science / Engineering or equivalent
Applied ML / experimentation systems experience is advantageous
Frontend / UI experience is advantageous
Experience with Docker, Kubernetes, and ArgoCD is advantageous
Infrastructure-as-code experience with Pulumi or Terraform is advantageous

Benefits

Comp & perks

High-ownership environment with autonomy and accountability
Opportunity to shape architecture and ship features to production
Work alongside engineering leadership, a VP Product, and senior data scientists
Exposure to data pipelines, ML and algorithms, backend services, and UI
Opportunity to build a brand-new revenue stream
Professional growth through independent learning and exploration of new fields