•We are looking for an AI Platforms Engineer to design, build, and operate the foundational platform that enables teams to develop, deploy, govern, and scale AI solutions reliably and securely. This role sits at the intersection of platform engineering, MLOps, infrastructure, data, and developer enablement.
+ ' ' + Strong experience with Kubernetes and containerized workloads in production5+ years experience in production infrastructure as a Platform, SRE, DevOps, or MLOps engineerStrong scripting and automation in Go and/or Python — enough to write a Kubernetes controller, or a non-trivial operational toolExperience with CI/CD pipelines, Infrastructure-as-code and GitOps: Gitlab CI, Terraform, Ansible, Helm, ArgoCD or FluxSolid understanding of Linux, networking, storage, and securityExperience with monitoring and observability tools such as Prometheus, Grafana, OpenTelemetryUnderstanding of the ML lifecycle: training, deployment, inference, evaluation, and monitoringExperience building or operating shared platforms used by multiple teamsAbility to work closely with data scientists, ML engineers, software engineers, and security teamsDepth in at least one of
•platform SRE at scale (multi-tenant Kubernetes, 99.9%+ SLOs, capacity planning)
•MLOps (model registry, deployment pipelines, canary and shadow rollouts, evaluation, Langfuse or equivalent LLM observability)
or API gateway operations (Kong, Envoy, or Istio at production scale, plugin development, request-path performance tuning)Nice to have
•Experience with LLM / GenAI platformsExperience with model serving tools such as vLLM, Triton, TGI, Ray, KServe, or TorchServeFamiliarity with RAG, embeddings, reranking, and vector databasesExperience with GPU infrastructure and scheduling AI workloadsExperience integrating open-source models and commercial AI APIsExperience with identity and access management such as LDAP, SAML, OIDC, OAuth2 + ' ' + Opportunities for professional growth and development.Competitive salary and bonuses.Comprehensive insurance coverage.Supportive work environment.Visa Premium salary card.Corporate discounts and events.Additional vacation days.Discounted education and employee loans. + ' ' + Design and build scalable AI platform capabilities for training, fine-tuning, inference, evaluation, and experimentation.
Uyğunluğunuzu görün
Daxil olun və CV-nizi yükləyin, AI bu elana uyğunluğunuzu analiz edib məsləhət versin.
•model serving,vector databases,feature/data access,prompt and agent workflows, GPU workload orchestration,secrets and configuration management.Build reusable MLOps/LLMOps pipelines for model packaging, deployment, rollback, versioning, and lifecycle management.
Enable secure deployment and operation of
•open-source models, commercial model APIs, retrieval-augmented generation systems, agent-based workloads.Create internal self-service tooling, templates for AI application teams.
Implement platform controls for
•authentication and authorization, rate limiting and quota management, audit logging, data protection, policy enforcement, guardrails.
Build observability for AI workloads, including
•latency,throughput,token usage,GPU utilization,model/system health,drift and quality indicators.Improve reliability and efficiency of AI infrastructure through automation, SRE practices, and performance tuning.Partner with data scientists, software engineers, architects, security teams, and business stakeholders to translate AI use cases into robust platform capabilities.Define standards and best practices for AI platform architecture, CI/CD, monitoring, governance, and operations.Support evaluation and integration of emerging AI infrastructure technologies, frameworks, and tools.Kapital Bank iş mühiti, əlavə fürsətlər və digər vakansiyaları görüntüləmək üçün Kapital Bank Life səhifəsinə keçid edin. Vakansiyalardan daha tez xəbərdar olmaq üçün Telegram kanalımıza abunə olun!