Senior Specialist - AI Engineering

Senior AI Platform Engineer Role Overview We are seeking a Senior AI Platform Engineer with overall 7 to 10 years of experience to design build and operate a secure scalable enterprise AI platform on Microsoft Azure primarily hosted on Azure Kubernetes Service AKS The role requires a strong platform engineering mindset combining AI engineering cloudnative engineering DevSecOps LLMOps security automation observability and operational excellence The engineer will create reusable platform capabilities that enable teams to build and productionize generative AI RAG and agentic AI solutions efficiently Key Responsibilities Design build and operate scalable AI platform capabilities on Azure and AKS Engineer capabilities for LLM applications RAG solutions AI agents multiagent workflows AI gateways guardrails and model evaluation Develop reusable platform services APIs deployment templates and reference implementations Build agent harness capabilities covering orchestration tool integration memory context management state management policy enforcement tracing and exception handling Enable secure integration with enterprise tools and data sources using Model Context Protocol MCP APIs connectors and eventdriven patterns Build reusable RAG pipelines covering document ingestion chunking embeddings vector indexing retrieval reranking grounding and citations Implement vector database and enterprise search capabilities using technologies such as Azure AI Search PostgreSQL with pgvector or equivalent platforms Implement centralized AI guardrails for prompt injection unsafe content sensitivedata exposure inappropriate tool execution and unauthorized access Establish CICD and Infrastructure as Code practices using GitHub GitHub Actions Terraform and container technologies Embed security testing container scanning dependency scanning policy validation AI evaluation and guardrail testing into delivery pipelines 
 Implement endtoend observability for infrastructure applications LLM calls token consumption RAG pipelines agent workflows security events and costs 
 Apply SRE practices covering availability performance capacity incident response resilience disaster recovery and automated remediation 
 Provide selfservice onboarding golden paths sample repositories documentation and operational runbooks for engineering teams 
 Collaborate with architects AI engineers developers security risk data and operations teams to establish enterprise AI platform standards 
 Primary Skills 
 Microsoft Azure and Azure Kubernetes Service 
 Kubernetes Docker and container orchestration 
 Azure OpenAI and Microsoft Foundry 
 Large Language Models and generative AI 
 Agentic AI and multiagent systems 
 Agent harness and orchestration engineering 
 Model Context Protocol and tool integration 
 RetrievalAugmented Generation Embeddings vector search and vector databases Azure AI Search PostgreSQL and pgvector AI gateways model gateways and API Management AI guardrails content safety and responsible AI Prompt model RAG and agent evaluation LLMOps MLOps and AI observability GitHub GitHub Actions and DevSecOps Terraform Bicep and Infrastructure as Code Entra ID managed identity RBAC Key Vault and private networking Azure Monitor Application Insights OpenTelemetry Prometheus and Grafana Python and any other programming language like Java C LangChain LangGraph Semantic Kernel AutoGen or equivalent frameworks Required Qualifications Strong experience in building an enterprise AI platform cloud engineering DevOps SRE or distributed systems Practical experience with LLMs RAG embeddings vector databases AI agents MCP guardrails and AI evaluation Experience with Azure AI Search Azure API Management Azure Container Registry Key Vault and Azure monitoring services Experience with LangChain LangGraph Semantic Kernel MCP servers agent registries tool catalogs or model gateways Experience implementing multitenant AI platforms with workload identity network data and cost isolation Familiarity with AI governance privacy model risk management threat modeling and regulatory controls Handson experience designing and operating production workloads on Azure and AKS Strong knowledge of Kubernetes networking security scaling identity observability and workload isolation Experience building automated delivery pipelines using GitHub Actions and Infrastructure as Code Strong understanding of APIs microservices eventdriven integration authentication authorization and secure software development Experience operationalizing production platforms with defined availability performance security and support requirements Proficiency in at least one modern programming language Strong troubleshooting documentation collab