AI DevOps Engineer (AWS · MLOps · Remote)

About the role

CloudiQS is hiring a fully remote AI DevOps Engineer (4–8 yrs) for AWS-native MLOps work — SageMaker, Bedrock, Lambda, EKS — with CI/CD, IaC, and model-drift observability. Work from anywhere in India. Direct apply: hello@cloudiqs.com.

CloudiQS, a 2026-era AI-first infrastructure firm, is hiring senior AI DevOps Engineers to design and operate the production layer behind generative AI, computer vision, and NLP workloads. The fully remote role centres on AWS-native AI services — SageMaker for ML lifecycle, Bedrock for foundation models, Lambda + ECS/EKS for inference — wired together with CI/CD (CodePipeline/Jenkins) and Terraform-managed multi-region infrastructure. Strong cross-functional collaboration with data scientists, with on-call rotation and US/EU-timezone overlap.

Responsibilities

Design and operate CI/CD pipelines for ML models on AWS CodePipeline, CodeBuild, Jenkins. Manage AWS infrastructure for AI workloads — EC2, S3, SageMaker, Bedrock, Lambda, ECS/EKS. Wire observability for model performance and drift detection (CloudWatch + Prometheus + Grafana + AI-specific tooling). Author Terraform modules for cost-optimised, multi-region AI environments. Collaborate with data scientists on text / image / agentic AI deployments. Implement blue-green deployments, chaos engineering, and cost guardrails for large-scale training and inference. Ensure IAM, VPC, encryption, and compliance hygiene end to end.

Requirements & qualifications

4–8+ years of DevOps / Cloud experience with strong AWS focus. AWS DevOps Engineer Professional or Solutions Architect certifications preferred. Hands-on Docker, Kubernetes (EKS), Terraform, Ansible, Python and Bash scripting. MLOps practice with SageMaker, MLflow, or Kubeflow for model lifecycle. Working knowledge of Generative AI tooling — AWS Bedrock, OpenAI integrations, prompt engineering. Strong Linux, networking, and security fundamentals. Excellent written and verbal English for fully async remote collaboration. Bachelor's / Master's in CS, Engineering, or equivalent practical experience.

Why this role in 2026

AI + DevOps is the fastest-growing speciality in Indian remote tech in 2026. CloudiQS's focus on production AWS Bedrock / SageMaker means you ship infra that real customers depend on — not lab toys. Remote-first culture removes Hyderabad / Bangalore / Pune relocation friction. The certification stipend and exposure to generative AI tooling compound into one of the most resume-strong combos for 2027 hiring.

Application tips

Email hello@cloudiqs.com with subject "AI DevOps Engineer — AWS · Remote · May 2026 Application". Highlight any production MLOps work (SageMaker pipelines, Bedrock integrations, model-drift detection) with a GitHub link or architecture writeup. Alternative: search "AI DevOps Engineer AWS CloudiQS" on Indeed or Glassdoor for the active posting. Include AWS Bedrock or SageMaker side projects prominently — they are the single strongest selection signal.

Interview preparation

Expect deep AWS architecture rounds: "Design SageMaker training + inference for a multi-tenant SaaS", "What is model drift and how do you detect it in production?", "Compare Bedrock vs OpenAI for a customer-facing chat app", "How would you secure an LLM behind API Gateway?". Be ready to whiteboard end-to-end IaC for a Lambda + ECS/EKS + SageMaker workload. Prepare on AWS Well-Architected, MLOps maturity model, and cost optimisation patterns (Spot, Savings Plans, Bedrock per-token pricing).

Career growth

Realistic next step after 2 years here: Senior AI Infrastructure Engineer at ₹18–28 LPA, or Staff DevOps at fast-growing AI startups (Cohere India, OpenAI India ops, etc.). Generative AI infra is one of the highest-leverage specialisations through 2027 — AWS Bedrock / SageMaker + Kubernetes + Terraform compounds into ₹35–55 LPA range within 4 years.

Company & benefits

₹10–17 LPA salary band depending on experience and certification stack. Fully remote, flexible US/EU-overlap hours. Health insurance, certification stipends (AWS / GCP), and exposure to production generative AI projects. Work-life balance with no relocation. Async collaboration with global teams. Performance bonuses and growth track to senior architect roles.