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Kigroup

MLOps Engineer – Azure & AI/ML Platforms (all genders)

  • Seen live on Kigroup's site 3 days ago
  • Mid level
Pay
Not stated
Location
Cologne, Nordrhein-Westfalen, Germany
Open for
13+ days
First seen
Oct 22, 2026
Apply on Kigroup's site (opens in a new tab)

Posting record

No flags

Open 13+ days

The posting's record, oldest first
  1. Already up when Ghostless started watching Kigroup
  2. Last checked: still up
How we know

It hasn't been reposted, listed twice, or left up unusually long, and the posting doesn't say it's a talent pool.

Ghostless records the day it first sees a posting, so a repost can't reset its age. This one was already up when Ghostless started tracking Kigroup, so its true age is longer.

Last checked Nov 1, 2026.

How well do you match?

See how much of this posting your resume shows, and what it's missing.

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What the posting discloses

Not stated: Pay, real vacancy, AI screening.

Why these three

Ontario requires postings from employers with 25 or more staff to state the pay, whether the vacancy exists, and whether AI screens applicants.

Some employers add pay only on their own site. Check the original posting before you rule it out.

Skills mentioned

About the role

🚀 Become our new MLOps Engineer (all genders)

At KI Performance , we move AI from experimentation to production. As a MLOps Engineer , you will design, build, and operate highly scalable, secure Azure-based AI platforms used in production environments. This role sits at the intersection of cloud infrastructure, DevOps, and AI delivery , with a strong focus on enabling iterative AI development , reliable model deployment , and platform scalability .

You will work closely with AI engineers, data teams, and product stakeholders to ensure that AI use cases can be developed, deployed, and operated efficiently at scale — with production-grade reliability, security, and observability.

Your responsibilities

Cloud Infrastructure & Platform Engineering

  • Design, implement, and operate scalable Azure infrastructure for AI and data-intensive platforms using Terraform
  • Build and maintain secure Azure networking architectures (VNETs, subnets, NSGs, Private Endpoints)
  • Implement access control and governance using Azure RBAC, Key Vault, and Azure Policies
  • Ensure infrastructure is production-ready with a focus on performance, reliability, and scalability

CI/CD & Release Engineering

  • Design and operate modern CI/CD pipelines using GitHub Actions
  • Enable fast, safe, and repeatable deployments for infrastructure, services, and AI models
  • Support iterative development with strong versioning, testing, and rollback strategies

MLOps & AI Platform Enablement

  • Operationalize AI use cases using MLflow (experiment tracking, model registry, deployment workflows)
  • Support the full AI lifecycle from experimentation to production deployment
  • Deploy and operate model inference services exposed via REST APIs (FastAPI preferred)
  • Collaborate closely with AI engineers to ensure models are production-ready

Observability & Reliability

  • Implement end-to-end observability using OpenTelemetry
  • Set up monitoring and logging using Azure Application Insights (or equivalent tooling)
  • Proactively improve system reliability, performance, and incident response

Engineering & Automation

  • Use Python for automation, AI integration, backend services, and tooling
  • Support platform self-service capabilities for engineering teams
  • Continuously improve infrastructure and operational maturity

Your profile

  • Hands-on experience building Azure infrastructure for scalable AI platforms using Terraform
  • Strong experience designing CI/CD pipelines with GitHub Actions
  • Proven experience with OpenTelemetry and monitoring using Azure Application Insights
  • Strong MLOps experience using MLflow (tracking, registry, deployment workflows)
  • Strong Python skills for AI development, automation, and backend integration
  • Experience exposing AI inference services via REST APIs (FastAPI preferred)
  • Deep understanding of Azure networking (VNETs, subnets, NSGs, Private Endpoints)
  • Strong knowledge of Azure security and governance (IAM/RBAC, Key Vault, Azure Policies)

Nice to have

  • Experience with Agentic AI platforms
  • Hands-on experience with Microsoft Foundry / Azure AI Foundry
  • Experience using LangGraph or other GenAI development frameworks
  • Knowledge of vector databases and retrieval systems (Azure AI Search preferred)
  • Experience with cost optimization strategies for Azure AI infrastructure

Why join us

  • Work with a highly skilled Engineering, Data & AI team
  • Flexible hybrid setup
  • Lots of ownership and freedom to shape solutions
  • Access to modern cloud, data & AI technologies
  • Personal development, training budget, certifications
  • A culture built on trust, autonomy, and collaboration

About KI performance

At KI performance, we help organizations use data, software, and artificial intelligence to solve complex business challenges and prepare for an AI-driven future.

Our work ranges from enterprise data platforms and cloud architectures to AI-enabled applications, intelligent workflows, and production-grade GenAI solutions. We work closely with leading enterprises and technology partners to build solutions that are technically robust, operationally sustainable, and connected to measurable business value.

Our culture is shaped by curious, hands-on people who enjoy taking ownership, learning quickly, and building meaningful solutions together.

Different perspectives make better teams.

We welcome applications from everyone, regardless of gender identity, ethnic or social background, religion or belief, disability, age or sexual orientation. What matters to us is what you bring to the team and what you want to build with us.

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