{"id":1272842,"url":"https://alion.io/job/norwin-technologies-senior-infrastructureplatform-engineer","title":"Senior Infrastructure/Platform Engineer","company":{"id":3808915,"name":"Norwin Technologies","domain":"norwintechnologies.com","url":"https://alion.io/company/norwin-technologies","size_band":"11-50","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":null,"truth_index":null},"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":18500,"max_usd":42000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":40},"experience_years_min":8,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"CI/CD","optional":false},{"name":"CUDA","optional":false},{"name":"CUDA Toolkit","optional":false},{"name":"GCP","optional":false},{"name":"GitOps","optional":false},{"name":"KServe","optional":false},{"name":"Kubernetes","optional":false},{"name":"Linux","optional":false},{"name":"LLM","optional":false},{"name":"Platform Engineering","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"Ray Serve","optional":false},{"name":"Terraform","optional":false},{"name":"Triton Inference Server","optional":false},{"name":"Ray","optional":true}],"status":"live","first_seen_at":"2026-08-31T08:31:48Z","employer_posted_date":null,"last_verified_at":"2026-08-31T08:31:48Z","board_verified":false,"closed_at":null,"days_open":41,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":41},"description":"Job Description:\n\nJob Role:\n\nSenior Infrastructure Engineer / Platform Engineer AI Platforms & GPU Infrastructure\n\nJob Summary:\n\nWe are looking for a hands-on Infrastructure Engineer / Platform Engineer with 8+ years of experience building and operating cloud-native platforms for Agentic AI workloads. The ideal candidate should have deep expertise in Kubernetes, Terraform, CI/CD, Infrastructure as Code, Multi-Cloud environments, and proven experience deploying Generative AI, Agentic AI, and LLM workloads on GPU infrastructure. Experience supporting production-scale AI platforms, model serving, and MLOps is essential.\n\nKey Responsibilities:\n\n- Design, build, and operate scalable Kubernetes platforms for AI/ML and GenAI workloads.\n\n- Automate cloud infrastructure provisioning using Terraform and Infrastructure as Code.\n\n- Build and maintain CI/CD pipelines and GitOps deployment frameworks.\n\n- Deploy and manage GPU-enabled infrastructure supporting model training and inference.\n\n- Support Large Language Models (LLMs), RAG pipelines, and Agentic AI applications in production.\n\n- Build scalable AI serving platforms using Kubernetes-based model serving frameworks.\n\n- Implement monitoring, observability, security, and platform reliability best practices.\n\n- Partner with AI/ML engineers and data scientists to accelerate AI adoption.\n\n- Drive platform automation and self-service capabilities across cloud environments.\n\nRequired Skills:\n\n- 8+ years of experience in Platform Engineering\n\n- Strong hands-on experience with Kubernetes in large-scale production environments.\n\n- Expertise in Terraform and Infrastructure as Code (IaC).\n\n- Strong experience with CI/CD, GitOps, and automation.\n\n- Experience across AWS, Azure, and/or GCP environments.\n\n- Strong Linux administration and troubleshooting skills.\n\n- Proficiency in Python and/or Go.\n\nMandatory Experience:\n\n- Hands-on experience deploying AI/ML, Generative AI, or Agentic AI solutions in production.\n\n- Experience deploying and scaling LLM workloads.\n\n- Strong experience with GPU infrastructure including NVIDIA GPUs, CUDA, GPU Operators, and model optimization.\n\n- Experience with AI model serving platforms such as Triton Inference Server, KServe, Ray Serve, or similar.\n\n- Experience building RAG pipelines and AI platforms.\n\n- Experience with vector databases and AI orchestration frameworks.\nSkills\nIT Infrastructure, Kubernetes, Terraform, CI/CD, CI/CD Pipeline, LLM, 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