GenAI Platform Engineer

Description

Summary: Join Accenture Technology as a GenAI Platform Engineer to build, operate, and scale enterprise-grade Generative AI platforms, enabling the development and execution of AI agents. Highlights: 1. Build, operate, and scale enterprise-grade Generative AI platforms 2. Deliver reliable, secure, and high-performing AI infrastructure 3. Work with cutting-edge GenAI technologies and practices **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 **Responsibilities** * 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 **Working Model:** Hybrid