Senior AI Platform Engineer
This role is based in the Midcore District, a business unit within MTG that Plarium is part of. The Midcore District is home to six gaming studios: Plarium, InnoGames, Snowprint, Hutch, Ninja Kiwi, and Futureplay. Together, these studios make games played by tens of millions of people on mobile and PC.
The District isn’t just a holding structure. It offers studios a shared ecosystem covering marketing, data analytics, technology, player services, publishing, D2C distribution, and more so that they can focus on making great games.
As a Senior AI Platform Engineer in the AI Lab team, you will take ownership of Playamp's AI platform infrastructure and play a key role in enabling teams across the company to build and scale AI-powered solutions.
In this role, you will work closely with DevOps, Security, Engineering, and Product teams to support both production infrastructure and the development of Playamp's internal AI platforms.
As a Senior AI Platform Engineer in the AI Lab team, you will take ownership of Playamp's AI platform infrastructure and play a key role in enabling teams across the company to build and scale AI-powered solutions.
In this role, you will work closely with DevOps, Security, Engineering, and Product teams to support both production infrastructure and the development of Playamp's internal AI platforms.
14Responsibilities
Design, build, and operate Playamp's internal AI platform - model gateway, agent orchestration, RAG pipelines, vector stores, and the MCP servers that connect LLMs to our internal systems.
Productionize AI infrastructure on GCP (Vertex AI, GKE, managed and self-hosted inference) using Terraform and GitOps.
Bring AI to our DevOps and automationworkflows.
Own the agent lifecycle in production: registry, versioning, observability (tracing, evals, cost tracking), and regression gates.
Carry standard senior DevOps responsibilities alongside the team: production ownership, on-call, networking, security hardening, and incident response on AI platform's core infrastructure.
Develop guardrails that help the security teams track and monitor AI usage across the company.
What we expect
$14Desired
- Cost engineering for AI Practical experience managing AI spend in production - prompt and semantic caching, model selection trade-offs, batch vs real-time routing, per-team budgets and showback.
What we offer
Officially registered full-time employment
Paid annual leave according to local regulations
Medical support and paid leave
Individual development plan and regular feedback
Professional seminars, workshops, courses, and internal training programs
Reimbursement of gym membership fees
*Note: Benefits may vary by country.