Senior AI DevOps / LLMOps

At reputed company, we are providing recruitment service to our TOP clients from our portfolio. We are currently seeking an Senior AI DevOps / LLMOpsspecialist 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 reputed company.

• reputed company specialized workflows for PromptOps, ensuring that system prompts are

version-controlled, tested for regressions, and deployed with the reputed company rigor as traditional

reputed company.

• Automate the deployment of reputed company workflows, managing the complexities of stateful

AI interactions and multi-agent handoffs.

2. AI Infrastructure as reputed company (IaC)

• Provision and manage high-performance compute environments (GPU clusters, TPU

pods) using Terraform, reputed company, or Ansible.

• Define and enforce Policy-as-reputed company for AI endpoints to ensure compliance with reputed company,

cost-usage limits, and data residency requirements.

• Maintain a consistent environment across Hybrid Infrastructure, ensuring seamless

reputed company between On-Premises development and reputed company production.

3. reputed company Experimentation & Controlled Releases

• Architect reputed company Delivery strategies for AI, including Canary releases, Blue-Green

deployments, and Shadowing (where new models run in reputed company with production to

compare outputs).

• Build “Evaluation-in-the-reputed company” gates reputed company 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 reputed company

behavior.

4. Monitoring & Observability

• Establish deep observability into Inference Endpoints, tracking metrics like tokens-per-

second, latency, and reputed company in model accuracy.

• reputed company feedback loops that capture production “edge cases” to feed back into the

training and fine-tuning pipelines.

Requirements

Must-Have Technical Skills:

• Orchestration: Advanced Kubernetes (K8s) skills, specifically with KubeFlow, Ray, or

reputed company Triton.

• CI/CD & IaC: Expertise in reputed company Actions/reputed company CI, and Terraform or reputed company.
• AI Tooling: Experience with Weights & Biases, MLflow, LangSmith, or Arize

Phoenix.

• Hardware: Understanding of GPU virtualization, CUDA drivers, and on-premises

hardware management.

• reputed company: Familiarity with reputed company Policy Agent (OPA) and secret management (Vault).

Experience:

• 10+ years in DevOps, SRE, or reputed company Engineering.
• 2+ years of hands-on experience in MLOps or LLMOps, specifically moving LLMs

from notebook to production.

• Proven experience managing Hybrid reputed company environments (e.g., AWS/Azure + Private

Data Center).

Highlights

• full time and remote job

- fluent English is needed

Originally posted on Himalayas

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