Job Description
Procode Developer (GenAI / LLM Engineer) Role Overview The Procode Developer (GenAI / LLM Engineer) will play a critical role in designing, building, and delivering enterprise-grade Generative AI solutions on Microsoft Azure. This role is focused on translating business use cases into secure, scalable, and production-ready AI systems that deliver measurable business value while meeting enterprise governance, security, and compliance standards. Key Responsibilities Enterprise AI Solution Delivery β’ Design and implement GenAI solutions using Azure OpenAI and Azure AI Foundry β’ Build retrieval-augmented generation (RAG) architectures β’ Develop agentic AI systems for enterprise use cases β’ Implement prompt engineering, orchestration, and tool/function calling Platform & Architecture Enablement β’ Design cloud-native, scalable AI architectures on Azure β’ Integrate AI services with enterprise systems and data platforms β’ Support modernisation and AI platform enablement initiatives Governance, Security & Compliance β’ Implement responsible AI (RAI) controls and safety guardrails β’ Align solutions with enterprise security, compliance, and governance frameworks β’ Support model evaluation, monitoring, and auditability Delivery & Transformation Support β’ Work with client stakeholders across business, IT, and leadership β’ Support agile delivery models and enterprise programs β’ Enable knowledge transfer, documentation, and internal capability building Core Capabilities Provided β’ GenAI platform engineering β’ LLM application development β’ Enterprise AI architecture β’ Agentic system design β’ AI governance & safety β’ Cloud-native delivery β’ DevOps & MLOps enablement Technology Landscape β’ Languages: Python β’ AI Platforms: Azure OpenAI, Azure AI Foundry β’ Azure Services: AI Search, Functions, Key Vault, Event Grid, Service Bus, Storage, App Service, Container Apps β’ Frameworks: Semantic Kernel, LangGraph, AutoGen β’ DevOps: Git, CI/CD, Observability (App Insights, Log Analytics) β’ Data: Vector DBs, embeddings, RAG pipelines Engagement Outcomes β’ Production-ready AI solutions β’ Secure enterprise AI platform β’ Scalable AI architecture β’ Measurable business value β’ Accelerated AI adoption β’ Sustainable internal capability Apply tot his job