{"id":1238951,"url":"https://alion.io/job/funic-tech-private-limited-senior-azure-cloud-engineer","title":"Senior Azure Cloud Engineer","company":{"id":3800661,"name":"FUNIC TECH PRIVATE LIMITED","domain":"funictech.com","url":"https://alion.io/company/funic-tech-private-limited","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Schema","truth_index":{"grade":"D","score":40,"open_postings":13,"ghost_share":1,"stale_share":0,"repost_share":0,"time_to_fill_p50_days":null,"computed_at":"2026-10-01T05:45:00Z"}},"role":"DevOps","role_family":"DevOps","seniority":"senior","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Bengaluru, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":17000,"max_usd":39000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":42},"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Azure","optional":false},{"name":"Azure AKS","optional":false},{"name":"Azure DevOps","optional":false},{"name":"CI/CD","optional":false},{"name":"Databricks","optional":false},{"name":"Docker","optional":false},{"name":"GitHub Actions","optional":false},{"name":"GitOps","optional":false},{"name":"IAM","optional":false},{"name":"Jenkins","optional":false},{"name":"Kubernetes","optional":false},{"name":"Machine Learning","optional":false},{"name":"MLFlow","optional":false},{"name":"OpenShift","optional":false},{"name":"PowerShell","optional":false},{"name":"Python","optional":false},{"name":"Terraform","optional":false},{"name":"AI Agents","optional":true},{"name":"AIOps","optional":true},{"name":"ArgoCD","optional":true},{"name":"Grafana","optional":true},{"name":"Prometheus","optional":true},{"name":"RAG","optional":true}],"status":"live","first_seen_at":"2026-09-17T04:53:42Z","employer_posted_date":null,"last_verified_at":"2026-09-17T04:53:42Z","board_verified":false,"closed_at":null,"days_open":14,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":14},"description":"Senior Cloud Engineer - AI/ML\n\nExperience : 5 - 8 Years\n\nLocation : Bangalore\n\nWork Mode : Onsite\n\nJoining : Immediate to 15 Days\n\nJob Overview :\n\nWe are looking for an experienced Senior Cloud Engineer - AI/ML with strong hands-on expertise in Azure, Databricks, Kubernetes, AKS, ARO, Terraform, MLflow, CI/CD, and Python.\n\nThe ideal candidate will be responsible for supporting ML/AI development teams and building scalable, secure, and automated cloud infrastructure and deployment workflows. The role involves driving end-to-end automation for machine learning model deployment, MLOps, infrastructure provisioning, monitoring, and operations across Azure, Databricks, and Kubernetes platforms.\n\nKey Responsibilities :\n\n- Design, build, and maintain CI/CD and Continuous Training (CT) pipelines for ML models using Azure DevOps, GitHub Actions, Jenkins, or similar tools.\n\n- Develop and manage deployment workflows for Databricks Jobs, MLflow models, APIs, and microservices.\n\n- Deploy and operate ML workloads on Azure Kubernetes Service (AKS) and Azure Red Hat OpenShift (ARO).\n\n- Automate cloud infrastructure provisioning and configuration using Terraform, Python, Bash, PowerShell, and Infrastructure as Code (IaC) practices.\n\n- Implement GitOps-based deployment and infrastructure management wherever applicable.\n\n- Manage and optimize Azure Databricks workspaces, clusters, compute resources, and related cloud services.\n\n- Configure and maintain AKS/ARO clusters, networking, ingress, storage, secrets, and model-serving environments.\n\n- Build scalable and reliable environments for ML model training, deployment, inference, and monitoring.\n\n- Implement monitoring, logging, alerting, and observability for cloud and ML workloads.\n\n- Troubleshoot infrastructure, deployment, Kubernetes, networking, and application-related issues.\n\n- Collaborate closely with ML Engineers, Data Engineers, Data Scientists, DevOps Engineers, and Application Teams.\n\n- Implement best practices for cloud security, identity and access management, governance, compliance, and cost optimization.\n\n- Support production deployments and ensure high availability, scalability, and reliability of AI/ML workloads.\n\n- Continuously improve automation, deployment processes, and operational efficiency.\n\nRequired Skills :\n\n- 5 - 8 years of experience in Cloud Engineering, DevOps, MLOps, or related roles.\n\n- Strong hands-on experience with Microsoft Azure.\n\n- Strong experience with Azure Kubernetes Service (AKS).\n\n- Experience with Azure Red Hat OpenShift (ARO).\n\n- Strong knowledge of Azure Databricks and Databricks deployment/management.\n\n- Hands-on experience with MLflow and ML model lifecycle management.\n\n- Strong understanding of Kubernetes-based application and model deployments.\n\n- Hands-on experience with Terraform / Infrastructure as Code (IaC).\n\n- Strong scripting/programming skills in Python.\n\n- Good knowledge of Bash and/or PowerShell.\n\n- Experience building and managing CI/CD pipelines using Azure DevOps, GitHub Actions, Jenkins, or similar tools.\n\n- Understanding of GitOps, containerization, Docker, Kubernetes, and automated deployments.\n\n- Good understanding of cloud networking, security, IAM, secrets management, and distributed systems.\n\n- Experience with monitoring and observability tools for cloud/Kubernetes environments.\n\nPreferred Skills :\n\n- Experience supporting AI/ML or MLOps platforms in enterprise environments.\n\n- Exposure to Generative AI, LLMs, Agentic AI, or RAG pipelines.\n\n- Experience deploying and managing AI/ML inference or model-serving workloads.\n\n- Knowledge of Azure AI services and cloud-native AI architectures.\n\n- Experience with GitOps tools such as Argo CD or Flux.\n\n- Knowledge of Prometheus, Grafana, Azure Monitor, Log Analytics, or similar monitoring platforms.\n\n- Experience with enterprise governance, security, compliance, and cost optimization.\nSkills\nAzure, Cloud Infrastructure, MLOps, AIOps, CI/CD, Azure Kubernetes Service, IAC Terraform, Kubernetes, PowerShell, Docker","description_format":"text","description_chars":4025,"description_truncated":false,"requirements":{"experience_years_min":5,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Commerce","Design & Creative","Web Design"],"lifecycle":[{"event":"open","at":"2026-09-25T16:00:00Z"}],"liveness":{"score":42,"band":"fade","label":"Fading","p_open":0.85,"p_active":0.547,"p_room":0.9,"age_days":14,"expected_fill_days":24,"reasons":["seen:14","stale_co","velocity","win:mid"],"computed_at":"2026-10-01T05:45:00Z"},"pay":null,"html_url":"https://alion.io/job/funic-tech-private-limited-senior-azure-cloud-engineer","json_url":"https://alion.io/job/funic-tech-private-limited-senior-azure-cloud-engineer.json","meta":{"generated_at":"2026-10-01T19:02:05Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","usage":{"tier":"search","counted_by":"address","units_charged":0,"used_today":0,"day_limit":null,"remaining_today":null,"minute_limit":null,"resets_at":"2026-10-02T00:00:00Z"}}}