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DevOps Engineer

DevOps Engineer

Tipstat®bangalore, karnataka, in
3 days ago
Job description

We are looking for a highly skilled DevOps Engineer with strong experience in DevSecOps and MLOps / LLMOps to design, automate, and secure our development and deployment pipelines.You will play a critical role in building scalable, secure, and production-ready infrastructure to support both traditional applications and machine learning / LLM workloads.This role demands a strong understanding of Kubernetes, CI / CD pipelines, infrastructure-as-code, model lifecycle management, and cloud-native security practices.

DevOps & Infrastructure

  • Design, implement, and manage scalable, fault-tolerant infrastructure on cloud or hybrid environments (AWS / GCP / Azure / Hetzner / Bare metal).
  • Develop and maintain CI / CD pipelines using tools like GitHub Actions , GitLab CI , Jenkins , or ArgoCD .
  • Manage containerized workloads using Kubernetes , Helm , and Docker .
  • Implement infrastructure as code (IaC) with Terraform / OpenTofu / Terragrunt .
  • Monitor system performance, availability, and cost efficiency using Prometheus, Grafana, ELK, or Loki .

DevSecOps

  • Integrate security automation into CI / CD pipelines (SAST, DAST, SCA, dependency scanning).
  • Implement policy as code using OPA / Conftest and enforce RBAC / IAM best practices.
  • Manage secrets and credentials using tools like Vault , Sealed Secrets , or External Secrets Operator .
  • Set up vulnerability scanning and runtime protection (e.g., Trivy, Falco, Aqua Security).
  • Define security baselines for infrastructure, network, and containers.
  • MLOps / LLMOps

  • Collaborate with ML and data teams to operationalize model training, evaluation, and deployment .
  • Build automated pipelines for data preprocessing, model training, and inference deployment using tools like Kubeflow, MLflow, or Airflow .
  • Manage feature stores, model registries, and monitoring for drift, latency, and accuracy.
  • Support LLM pipelines — prompt orchestration, fine-tuning, vector DB integrations, and retrieval-augmented generation (RAG) .
  • Optimize GPU-based workloads and manage distributed training / inference infrastructure.
  • Required Skills & Qualifications

  • Languages : Python, Bash, Go (preferred)
  • IaC Tools : Terraform / OpenTofu / Terragrunt
  • CI / CD : GitHub Actions, GitLab CI, Jenkins, ArgoCD
  • Containers : Docker, Kubernetes, Helm
  • Monitoring : Prometheus, Grafana, Loki, ELK
  • Security : Trivy, Falco, Vault, OPA, Snyk
  • MLOps Tools : MLflow, Kubeflow, Airflow, Weights & Biases
  • Cloud Platforms : AWS / GCP / Azure / Hetzner
  • Databases : PostgreSQL, Redis, Vector DBs (Milvus, Pinecone, Weaviate, Qdrant)
  • Nice to Have

  • Experience with GPU orchestration on Kubernetes (NVIDIA operator, KServe).
  • Exposure to LLM frameworks (LangChain, LlamaIndex, vLLM, Ollama).
  • Knowledge of data governance and compliance (GDPR, SOC2).
  • Experience with self-hosted runners , GitOps , or multi-cluster management .
  • Familiarity with event-driven systems (Kafka, NATS, or Redis Streams).
  • What We Offer

  • Opportunity to work on challenging, large-scale systems with real-world impact.
  • Collaborative team culture with focus on learning and innovation .
  • Competitive compensation and growth opportunities.
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    Engineer • bangalore, karnataka, in

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