Senior AI DevOps / LLMOps
- Remote
- Krakow, Podlaskie, Poland
- Krosno, Dolnośląskie, Poland
- Lublin, Lubelskie, Poland
- Poland, Mazowieckie, Poland
- Poznan, Wielkopolskie, Poland
- Warsaw, Warmińsko-Mazurskie, Poland
- Pilsen, Plzeňský kraj, Czechia
- Praha, Praha, Hlavní město, Czechia
- Riga, Rīga, Latvia
- Vilnius, Vilniaus apskritis, Lithuania
- Athens, Attikí, Greece
- Crete, Kríti, Greece
- Budapest, Budapest, Hungary
- Miskolc, Borsod-Abaúj-Zemplén, Hungary
- Brussels, Brussels, Belgium
- Liège, Walloon Region, Belgium
- Mons, Walloon Region, Belgium
- Namur, Walloon Region, Belgium
- Sofia, Sofia, Bulgaria
- Bordeaux, Nouvelle-Aquitaine, France
- Grenoble, Auvergne-Rhône-Alpes, France
- Lille, Hauts-de-France, France
- Lyon, Auvergne-Rhône-Alpes, France
- Montpellier, Occitanie, France
- Nantes, Pays-de-la-Loire, France
- Paris, Île-de-France, France
- Toulouse, Occitanie, France
- Baden-Baden, Baden-Württemberg, Germany
- Bad Homburg, Hessen, Germany
- Augsburg, Bayern, Germany
- Aachen, Nordrhein-Westfalen, Germany
- Bergisch Gladbach, Nordrhein-Westfalen, Germany
- Berlin, Berlin, Germany
- Bernau, Brandenburg, Germany
- Bielefeld, Nordrhein-Westfalen, Germany
- Bramsche, Niedersachsen, Germany
- Chemnitz, Sachsen, Germany
- Darmstadt, Hessen, Germany
- Darmstadt, Hessen, Germany
- Dresden, Sachsen, Germany
- Dresden, Sachsen, Germany
- Dusseldorf, Nordrhein-Westfalen, Germany
- Düsseldorf, Rheinland-Pfalz, Germany
- Essen, Nordrhein-Westfalen, Germany
- Frankfurt, Hessen, Germany
- Freiburg, Baden-Württemberg, Germany
- Geoergsmarienhütte, Niedersachsen, Germany
- Görlizt, Sachsen, Germany
- Göttingen, Niedersachsen, Germany
- Greifswald, Mecklenburg-Vorpommern, Germany
- Halle, Sachsen-Anhalt, Germany
- Hamburg, Hamburg, Germany
- Hannover, Niedersachsen, Germany
- Heinsberg, Nordrhein-Westfalen, Germany
- Karlsruhe, Baden-Württemberg, Germany
- Kiel, Schleswig-Holstein, Germany
- Koln, Nordrhein-Westfalen, Germany
- Leipzig, Sachsen, Germany
- Leverkusen , Nordrhein-Westfalen, Germany
- Lingen, Niedersachsen, Germany
- Magdeburg, Sachsen-Anhalt, Germany
- Mainz, Rheinland-Pfalz, Germany
- Mittenwalde , Brandenburg, Germany
- Munich, Bayern, Germany
- Münster, Nordrhein-Westfalen, Germany
- Münster, Nordrhein-Westfalen, Germany
- Neu-Ulm, Bayern, Germany
- Neuruppin, Brandenburg, Germany
- Neuss, Nordrhein-Westfalen, Germany
- Nuremberg, Bayern, Germany
- Osnabrück, Niedersachsen, Germany
- Paderborn, Nordrhein-Westfalen, Germany
- Potsdam, Brandenburg, Germany
- Quedlinburg, Sachsen-Anhalt, Germany
- Rimbach, Hessen, Germany
- Rostock, Mecklenburg-Vorpommern, Germany
- Schwerin, Mecklenburg-Vorpommern, Germany
- Stuttgart, Baden-Württemberg, Germany
- Ulm, Baden-Württemberg, Germany
- Varel, Niedersachsen, Germany
- Viechtach, Bayern, Germany
- Warendorf, Nordrhein-Westfalen, Germany
- Wiesbaden, Hessen, Germany
- Wuppertal, Nordrhein-Westfalen, Germany
- Lisbon, Lisboa, Portugal
- Porto, Lisboa, Portugal
- Zagreb, Zagrebačka županija, Croatia
- Zagreb, Grad Zagreb, Croatia
- Sarajevo, Federacija Bosne i Hercegovine, Bosnia and Herzegovina
+88 more- Engineering
- full time and remote job
- fluent English is needed
Job description
At TechBiz Global, we are providing recruitment service to our TOP clients from our portfolio. We are currently seeking an Senior AI DevOps / LLMOps specialist to join one of our clients' teams. If you're looking for an exciting opportunity to grow in a innovative environment, this could be the perfect fit for you.
Key Responsibilities
Automation of Build-to-Production
- Design and implement robust CI/CD pipelines tailored for AI, covering model weights,
dataset versioning, and application code.
- Develop specialized workflows for PromptOps, ensuring that system prompts are
version-controlled, tested for regressions, and deployed with the same rigor as traditional
code.
-Automate the deployment of Agentic workflows, managing the complexities of stateful
AI interactions and multi-agent handoffs.
2. AI Infrastructure as Code (IaC)
- Provision and manage high-performance compute environments (GPU clusters, TPU
pods) using Terraform, Pulumi, or Ansible.
- Define and enforce Policy-as-Code for AI endpoints to ensure compliance with security,
cost-usage limits, and data residency requirements.
- Maintain a consistent environment across Hybrid Infrastructure, ensuring seamless
parity between On-Premises development and Cloud production.
3. Safe Experimentation & Controlled Releases
- Architect Progressive Delivery strategies for AI, including Canary releases, Blue-Green
deployments, and Shadowing (where new models run in parallel with production to
compare outputs).
- Build “Evaluation-in-the-Loop” gates within the pipeline to automatically test for bias,
hallucination, and performance degradation before a release.
- Implement A/B testing frameworks specifically designed for LLM outputs and agentic
behavior.
4. Monitoring & Observability
- Establish deep observability into Inference Endpoints, tracking metrics like tokens-per-
second, latency, and drift in model accuracy.
-Integrate feedback loops that capture production “edge cases” to feed back into the
training and fine-tuning pipelines.
Job requirements
Must-Have Technical Skills:
-Orchestration: Advanced Kubernetes (K8s) skills, specifically with KubeFlow, Ray, or
NVIDIA Triton.
-CI/CD & IaC: Expertise in GitHub Actions/GitLab CI, and Terraform or Pulumi.
- AI Tooling: Experience with Weights & Biases, MLflow, LangSmith, or Arize
Phoenix.
-Hardware: Understanding of GPU virtualization, CUDA drivers, and on-premises
hardware management.
-Security: Familiarity with Open Policy Agent (OPA) and secret management (Vault).
Experience:
- 10+ years in DevOps, SRE, or Cloud Engineering.
- 2+ years of hands-on experience in MLOps or LLMOps, specifically moving LLMs
from notebook to production.
-Proven experience managing Hybrid Cloud environments (e.g., AWS/Azure + Private
Data Center).
or
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