Software Engineer – Backend, Infra

GRAI

Backend and infrastructure engineer building production services, media pipelines, and ML infrastructure. Helping GRAI reimagine music discovery and sharing through AI music products.

Posted 9/10/2026full-time🇵🇱 PolandMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates strong software engineering capabilities with a focus on building and maintaining production systems, particularly in AI and media processing. Proficient in Python and experienced with cloud infrastructure, distributed systems, and audio/video processing technologies.

Highest-signal resume keywords

Python ProgrammingDistributed SystemsAudio/Video ProcessingCloud InfrastructureModel Inference Optimization

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Software EngineeringData StructuresAlgorithmsClean Code PracticesDebugging Complex IssuesPerformance TradeoffsBackend ServicesAPIsJob QueuesDatabase Management

Soft Skills

Independent WorkTechnical Decision-MakingProject Ownership

Tools & Technologies

KubernetesDockerTerraformAWSGCPAzureFFmpegSparkRayPolars

Industry Keywords

AI Music ProductsMedia ProcessingTranscodingStreamingModel Serving

Tech Stack

Tools & technologies

AWSAzureC++CloudDistributed SystemsDockerFFmpegGoGoogle Cloud PlatformJavaKubernetesPythonRayRustSparkTerraformTypeScript

About the role

Key responsibilities & impact

Design, build, test, and maintain production software used in GRAI’s AI music products
Build backend services, APIs, workers, internal tools, and orchestration systems for media and AI pipelines
Work with audio/video processing systems, including formats, codecs, transcoding, metadata, storage, streaming, and delivery
Build and optimize systems around model inference, job queues, scheduling, batching, caching, retries, and observability
Own hard technical problems end-to-end and help shape the architecture as GRAI scales

Requirements

What you’ll need

Strong software engineering experience building production systems
Strong Python experience
Solid understanding of data structures, algorithms, complexity, and practical performance tradeoffs
Experience with distributed systems, backend services, APIs, queues, databases, object storage, and cloud infrastructure
Ability to debug complex issues across code, infrastructure, network, storage, and service boundaries
Experience writing clean, tested, maintainable code
Ability to work independently, make good technical decisions, and own projects end-to-end
Experience with one or more additional languages: Go, Rust, C++, Java, TypeScript, or similar
Experience with audio, video, media processing, codecs, containers, streaming, transcoding, FFmpeg, or similar systems
Experience with ML infrastructure, model serving, GPU workloads, inference optimization, batching, or distributed training/inference systems
Experience with cloud infrastructure, Kubernetes, Docker, Terraform, AWS/GCP/Azure/Nebius, or similar
Experience with data pipelines, object storage, large-scale file processing, WebDataset, S3-compatible storage, Spark/Ray/Polars/DuckDB, or similar

Benefits

Comp & perks

High ownership over important technical work
Be at the forefront of AI-driven music innovation
Opportunity to work on infrastructure at scale
Competitive compensation and equity
Flexibility in how you work