GenAI Platform Engineer

Accenture Technology powers our clients to achieve high performance. We combine business and industry insights with innovative technology to drive growth for your business. We extend our technology and business capabilities through a powerful alliance ecosystem of market leaders and innovators to provide our clients the best specialized skills and tailored solutions.

Job Summary

We are seeking a highly qualified professional to join our team as a GenAI Platform Engineer. As an essential part of our team, you will be responsible for building, operating, and scaling enterprise\-grade Generative AI platforms. You will work closely with the GenAI Platform Architect to deliver reliable, secure, and high\-performing infrastructure that enables the development and execution of AI agents.

Qualifications

• Strong proficiency in Python (minimum of 3 years), applying SOLID principles and best practices


• Hands\-on experience with Azure Cloud and Azure AI Services (Azure OpenAI, Azure AI Search, Azure Functions, APIM)


• Experience with RAG frameworks and ingestion pipelines (LangChain, LangGraph, LlamaIndex or equivalent)


• Knowledge of vector databases (Azure AI Search, pgvector, Chroma, Pinecone)


• Experience with REST APIs and enterprise system integrations (Jira, Confluence, GitHub)


• Solid understanding of DevOps and MLOps practices (Docker, Kubernetes, GitHub Actions, Azure DevOps, Terraform)


• Experience with identity and access management (Azure AD, OAuth2, RBAC)


• Familiarity with observability, monitoring, and performance optimization


• Strong problem\-solving skills and ability to work in distributed teams

• Implement and maintain the LLM gateway (model routing, cost control, failover, rate limiting)


• Develop internal SDK components, including agent abstractions, tool contracts, and memory/context interfaces


• Build and maintain RAG ingestion pipelines for code repositories, documentation, and knowledge bases


• Implement embeddings and vector store solutions with hybrid search (semantic \+ keyword)


• Develop Knowledge Graphs and enterprise adapters (Git, Jira, Confluence)


• Implement security controls such as output guardrails, sensitive data masking, RBAC, and prompt injection protection


• Configure agent sandboxing and integrate identity systems (Azure AD / OAuth2\)


• Set up observability frameworks including dashboards, structured logging, and productivity reporting


• Implement resilience mechanisms (circuit breakers, manual overrides, Human\-in\-the\-Loop via Teams)


• Develop evaluation benchmarks and continuous improvement feedback loops


• Integrate CI/CD pipelines for automated deployment of agents (GitHub Actions, ArgoCD)


• Integrate platform components with enterprise tools (Jira, Confluence, GitHub, Microsoft Teams)


• Manage cloud infrastructure (Azure AI Foundry / AWS Bedrock / Vertex AI) and optimize LLM cost and performance

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