AIOps Engineer

3 weeks ago


Gurugram Haryana India, IN Imaging IQ Full time
DevOps/AIOps Engineer (Platform)

Experience: 3–5 Years

About the Company

We aim to bring about a new paradigm in medical image diagnostics — intelligent, holistic, ethical, explainable, and patient‑centric. We’re looking for innovative problem‑solvers who empathize with clinicians and patients, understand business problems, and can design and deliver reliable, intelligent products.

Key Responsibilities

· CI/CD for services & models: Own pipelines (GitHub Actions/GitLab CI), environment gates, artifact/version governance (containers, models, SBOMs), safe rollouts & instant rollbacks.

· Kubernetes platform (EKS preferred): Operate multi-env clusters; Helm/Kustomize; GitOps (Argo CD/Flux); progressive delivery (canary/blue green/Argo Rollouts/Flagger).

· Serving & APIs: Deploy and tune FastAPI services and Triton/ONNX/TensorRT inference; traffic shaping, runtime config, autoscaling signals.

· Event-driven orchestration: Build robust consumers/producers on RabbitMQ/ActiveMQ/Kafka with back-pressure, dead-lettering, idempotency, and retry patterns.

· Observability & AIOps: Define SLIs/SLOs and error budgets; metrics/logs/traces (Prometheus/Grafana/Loki/Tempo/ELK); intelligent alerting & noise reduction; basic model/data drift hooks.

· Security in SDLC: Supply-chain security (image signing/provenance, SBOM scans), SAST/DAST/IaC scanning, policy-as-code (OPA/Gatekeeper), secrets hygiene in pipelines/workloads.

· Data/Model platform integration: S3/MinIO for artifacts; integrate model registry (MLflow or similar) into CD; immutable, traceable releases.

· Resilience & performance: Capacity planning (incl. GPU), autoscaling (HPA/VPA/KEDA), caching/queue tuning; chaos/game-days; write runbooks and own incident response for platform services.

· Developer experience: Golden paths, starter repos, internal Helm charts, docs & enablement to make shipping boring and fast.

· FinOps mindset: Cost dashboards, right-sizing, bin-packing, GPU utilization policies, spot vs on-demand strategy.

Skills and Qualifications (Required)

· 3+ years in DevOps/SRE/MLOps with strong Docker & Kubernetes fundamentals.

· Production CI/CD expertise; canary/blue-green; artifact & version management.

· IaC (Terraform) and GitOps workflows (Argo CD/Flux).

· Observability: Prometheus/Grafana; logs/traces with Loki/Tempo/ELK.

· Production message queues (RabbitMQ/ActiveMQ/Kafka) with back-pressure & retries.

· Cloud experience (AWS/GCP/Azure), EKS preferred; object storage (S3/MinIO); model registries (MLflow or similar).

· Security in SDLC and compliance guardrails for PHI-like data (least-privilege IAM, secrets, auditability).

· Incident response experience; writing SLIs/SLOs, runbooks, and operating to error budgets.

· Scripting for platform tasks (Python/Bash).

Preferred

· Triton Inference Server, ONNX/TensorRT optimizations; GPU scheduling on K8s (NVIDIA device plugin, MIG, node pools).


· Argo Rollouts/Flagger, Karpenter, KEDA; caching layers (Redis/NVCache patterns).

· Policy-as-code (OPA/Gatekeeper), image signing (cosign), SBOM tools (syft/grype).

· Network savvy for app delivery (ingress, service meshes, egress policies).

Education

BE/B.Tech (MS/M.Tech a bonus) or equivalent experience.

Location & Work Setup

On-site - Gurugram


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