Senior Backend (Python) Engineer

About the company:

A technology company at the intersection of enterprise Media Asset Management and generative AI, enabling companies to manage and simultaneously generate multimedia content at scale — including hyper-realistic digital humans and multilingual voice synthesis — is looking for a new addition to its new project.

The company's solutions are used by a diverse range of clients in entertainment, sports, healthcare and retail. Unlike a classic SaaS backend, this isn't just CRUD over a database — the core of the product is AI models and media processing in production deployment.

About the position:

We're looking for a Senior Backend Developer with real experience designing and running distributed systems in Python.

You won't just be "implementing tickets" — you will:

• design the architecture of backend services and data pipelines,
• influence technology decisions,
• work directly with ML engineers and the DevOps team on getting models into production,
• help set engineering standards.

The role is clearly backend-heavy. Frontend is only a marginal part (basic JavaScript / TypeScript occasionally comes in handy); the emphasis is on performance, scaling and production reliability.

Job description:

• Design and development of scalable backend services and REST APIs in Python
• Microservice and event-driven architecture
• Data pipelines for AI and media processing (video / audio)
• Integration of ML inference services into production systems
• Working with asynchronous queues and background processing
• Design of database schemas, caching layers and storage solutions (PostgreSQL, Redis)
• Performance optimization — low latency, high throughput
• Logging, monitoring, alerting and observability of production services
• Close collaboration with ML engineers and the DevOps team

Your impact:

• You'll be behind services that process large volumes of video and audio data
• You'll help bring generative AI models from research into production
• You'll influence what the infrastructure for digital humans and voice synthesis looks like
• Your architectural decisions will be visible in a product used by enterprise clients

Tech stack:

• Backend: Python
• API / architecture: REST API, microservices, event-driven systems
• Databases and cache: PostgreSQL, Redis
• Async processing: message / task queues
• Observability: logging, monitoring, alerting
• Additionally: JavaScript / TypeScript (basics)
• AI tooling: Copilot / Cursor / LLM APIs as part of the everyday workflow

Requirements:

• 5+ years of experience in software development
• Strong primary expertise in server-side Python
• Design and implementation of REST APIs and microservices
• Experience with event-driven architecture and asynchronous processing
• Good understanding of system design, scaling and performance optimization
• Hands-on knowledge of PostgreSQL and Redis
• Experience with monitoring and observability of production services
• Basics of JavaScript / TypeScript
• Comfortable working with AI tools (Copilot, Cursor, LLM APIs)
• English at a communicative level (B2+)

Nice to have:

• ML / inference: PyTorch, TorchServe, vLLM, Triton
• Orchestration and data: Airflow, Prefect, Temporal, async ETL, Parquet
• Media processing: FFmpeg, OpenCV
• Graphics: WebGL / Canvas
• Other: Neo4j, Kafka / RabbitMQ, AWS / GCP, Docker
• Background in media tech, graphics, VFX or computer vision
• Startup experience

What we offer:

• Fully remote cooperation within the EU / UK
• Freelance / contractor arrangement with flexible working hours
• Work on a product in the field of generative AI and enterprise media workflows
• A strong technical team — backend, ML research and DevOps under one roof
• Real architectural ownership, not just executing assignments
• An international environment and enterprise clients across multiple industries

Why this role is interesting:

It's not "another backend job."

You'll be tackling a combination that rarely comes together in a single role:

• distributed systems and scalable APIs,
• data pipelines for media processing,
• deploying generative AI models into production,
• performance, observability and production reliability.

If you enjoy backend work but want to be as close as possible to AI and media processing — this is exactly that type of role.