Scale AI

8 months ago

Software Engineer (Backend), Enterprise

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 2 hours agoStatus: Live

Job Summary

Backend-focused role building and scaling enterprise GenAI infrastructure. You’ll design and maintain scalable APIs and distributed data systems, deploy across hybrid/multi-cloud environments, and collaborate with ML, infra, and product teams to productionize GenAI models. You’ll work on reliable, high-performance backend systems that enable enterprise AI adoption at scale, shaping how large organizations deploy AI in production.

Location: Budapest

Workplace: Onsite

Employment Type: Full time

Job Function: Software Engineering

Key Responsibilities

•Design, build, and scale backend systems that power enterprise GenAI products and ensure reliability, performance, and deployment across Scale’s and customers’ infrastructure
•Develop core services and APIs that securely integrate AI models and enterprise data sources for production-scale adoption
•Architect scalable distributed systems for data processing, inference, and orchestration of large-scale GenAI workloads
•Optimize backend performance for latency, throughput, and cost across hybrid and multi-cloud environments
•Manage and evolve cloud infrastructure (AWS, Azure, or GCP), driving automation, observability, and security for large-scale AI deployments

Key Requirements

•4+ years of experience developing large-scale backend or infrastructure systems, with a focus on distributed services, reliability, and scalability
•Proficiency in Python or TypeScript with experience designing high-performance APIs using FastAPI, Flask, Express, or NestJS
•Deep familiarity with cloud infrastructure (AWS and Azure preferred) including Kubernetes and Docker, plus Terraform
•Experience managing data systems (PostgreSQL, DynamoDB, etc.) and building data pipelines for data-intensive applications
•Hands-on experience with GenAI applications, model integration, or AI agent systems; understanding how to deploy, evaluate, and scale AI workloads in production

Experience:4+ yearsGenAIBackendCloudDistributed systems

Skills:PythonTypeScriptFastAPIFlaskExpressNestJSKubernetesDockerTerraformPostgreSQLDynamoDBGenAICI/CDSecurityObservabilityMulti-cloud

Languages:English

Tech Stack:PythonTypeScriptFastAPIFlaskExpressNestJSKubernetesDockerTerraformPostgreSQLDynamoDBCI/CDAWSAzureGCPObservabilitySecurity

Company Brief

Scale AI

Provides data labeling, annotation, and infrastructure services to accelerate machine learning and AI development. Supplies high-quality training data, tooling, and APIs for customers in autonomous vehicles, mapping, robotics, and enterprise AI applications.

Industry: AI & Machine Learning

Company Size: Enterprise (1,001+ employees)

Growth: Scaleup

Valuation: Unicorn (USD 1B+)

Funding: Series E+

Headquarters: San Francisco, United States

Founded: 2016

Website LinkedIn

Loading job details...

Preparing the role view and application actions.

Scale AI

8 months ago

Software Engineer (Backend), Enterprise

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 2 hours agoStatus: Live

Job Summary

Location: Budapest

Workplace: Onsite

Employment Type: Full time

Job Function: Software Engineering

Key Responsibilities

•Design, build, and scale backend systems that power enterprise GenAI products and ensure reliability, performance, and deployment across Scale’s and customers’ infrastructure
•Develop core services and APIs that securely integrate AI models and enterprise data sources for production-scale adoption
•Architect scalable distributed systems for data processing, inference, and orchestration of large-scale GenAI workloads
•Optimize backend performance for latency, throughput, and cost across hybrid and multi-cloud environments
•Manage and evolve cloud infrastructure (AWS, Azure, or GCP), driving automation, observability, and security for large-scale AI deployments

Key Requirements

•4+ years of experience developing large-scale backend or infrastructure systems, with a focus on distributed services, reliability, and scalability
•Proficiency in Python or TypeScript with experience designing high-performance APIs using FastAPI, Flask, Express, or NestJS
•Deep familiarity with cloud infrastructure (AWS and Azure preferred) including Kubernetes and Docker, plus Terraform
•Experience managing data systems (PostgreSQL, DynamoDB, etc.) and building data pipelines for data-intensive applications
•Hands-on experience with GenAI applications, model integration, or AI agent systems; understanding how to deploy, evaluate, and scale AI workloads in production

Experience:4+ yearsGenAIBackendCloudDistributed systems

Skills:PythonTypeScriptFastAPIFlaskExpressNestJSKubernetesDockerTerraformPostgreSQLDynamoDBGenAICI/CDSecurityObservabilityMulti-cloud

Languages:English

Tech Stack:PythonTypeScriptFastAPIFlaskExpressNestJSKubernetesDockerTerraformPostgreSQLDynamoDBCI/CDAWSAzureGCPObservabilitySecurity

Company Brief

Scale AI

Industry: AI & Machine Learning

Company Size: Enterprise (1,001+ employees)

Growth: Scaleup

Valuation: Unicorn (USD 1B+)

Funding: Series E+

Headquarters: San Francisco, United States

Founded: 2016

Website LinkedIn