AI Platform Engineer

Plarium

Poland

On-site

PLN 240,000 - 360,000

Full time

1 hour ago
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Benefits offered by this job

Paid annual leave
Medical support
Individual development plan
Professional seminars and training
Gym membership reimbursement

Job summary

Plarium, within MTG's Midcore District, seeks a Senior AI Platform Engineer for the AI Lab to own Playamp's AI platform infrastructure and enable teams to build AI-powered solutions.

You will collaborate with DevOps, Security, Engineering, and Product teams to support production infrastructure and internal AI platforms, driving reliability and governance across the stack.

Qualifications

  • 5-7 years of Backend Engineering, infrastructure, DevOps or Platform Engineering in production, including 2+ years on AI infrastructure.
  • Experience with MCP and RAG: building or integrating MCP servers and exposing internal systems to LLMs.
  • Proven track record designing and shipping agentic systems with guardrails, retries and evaluation.

Responsibilities

  • Design, build, and operate Playamp's internal AI platform - model gateway, agent orchestration, RAG pipelines, vector stores, and MCP servers.
  • Productionize AI infrastructure on GCP (Vertex AI, GKE, managed and self-hosted inference) using Terraform and GitOps.
  • Bring AI to DevOps and automation workflows.
  • Own the agent lifecycle in production: registry, versioning, observability, and regression gates.
  • Carry standard senior DevOps responsibilities: production ownership, on-call, networking, security hardening, incident response on AI platform's core infrastructure.
  • Develop guardrails to help security track and monitor AI usage across the company.

Skills

Backend Engineering
Infrastructure
DevOps
Platform Engineering
AI infrastructure

Tools

Kubernetes
Networking
Terraform
CI/CD
GitOps
GCP
Vertex AI
GKE

Job description

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.

About the Role

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.

Responsibilities
  • 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 automation workflows.
  • 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.
Qualifications
  • 5-7 years of Backend Engineering\ infrastructure\ DevOps \ Platform Engineering in production, including 2+ years dedicated to AI infrastructure (real systems, not POCs).
  • Practical experience with the Model Context Protocol (MCP) and RAG - building or integrating MCP servers and exposing internal systems to LLMs.
  • Experience designing and shipping agentic systems in production: multi-step, tool-using agents with guardrails, retries, and evaluation.
  • Deep cloud experience, preferably GCP, with solid Kubernetes, networking, Infrastructure as Code (Terraform), CI/CD, and GitOps fundamentals.
  • AI evaluation infrastructure: Built or owned eval harnesses for LLMs/agents - golden datasets, offline + online evals, regression gates in CI, A/B testing of prompts and agents in production.
  • Strong Python. Hands-on with the modern LLM serving stack and at least one industry-standard agent framework (e.g., Google ADK, LangChain, or similar).
Required Skills
  • 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.
Equal Opportunity Statement

We are committed to diversity and inclusivity.

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