AI Platform Engineer

Plarium; Spain (TX); On-site; USD 140,000 - 200,000; Full time

Job summary

Playamp, part of MTG, seeks a Senior AI Platform Engineer to own the internal AI platform infrastructure and enable teams to build scalable AI-powered solutions. You will work with DevOps, Security, Engineering, and Product to support production infrastructure and internal AI platforms.

Responsibilities include designing and operating the internal AI platform, productionizing infra on GCP with Terraform and GitOps, and owning agent lifecycles while implementing guardrails and security hardening

Qualifications

• 5–7 years in infra/DevOps or platform engineering, with 2+ years in AI infra.
• Experience with MCP and RAG in real systems, not POCs.
• Proven design and delivery of production-grade agentized systems with guardrails.
• Strong GCP, Kubernetes, networking, IaC (Terraform), CI/CD, GitOps.
• Hands-on Python and LLM serving stacks; one agent framework (LangChain or similar).

Responsibilities

• Design, build, and operate Playamp's internal AI platform components.
• Productionize AI infra on GCP using Terraform and GitOps.
• Integrate AI into DevOps and automation workflows.
• Own agent lifecycle: registry, versioning, observability, regression gates.
• Handle production ownership, on-call, networking, security hardening, incident response for AI infra.
• Develop guardrails to monitor AI usage across the company.

Skills

DevOps

GCP

Kubernetes

Terraform / IaC

Python

RAG pipelines

MCP protocol

Agent frameworks

Tools

LangChain

Google ADK

LLM serving stack

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 infrastructure, DevOps, or 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.