platform engineer

Accenture Technology provides business and industry insights combined with innovative technology to drive client growth. The organization leverages a powerful alliance ecosystem of market leaders and innovators to deliver specialized skills and tailored solutions.

• Implement and maintain the LLM gateway including model routing, cost control, failover, and rate limiting;
• Develop internal SDK components such as 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;
• Develop Knowledge Graphs and enterprise adapters for Git, Jira, and Confluence;
• Implement security controls including output guardrails, sensitive data masking, RBAC, and prompt injection protection;
• Configure agent sandboxing and integrate identity systems;
• Set up observability frameworks including dashboards, structured logging, and productivity reporting;
• Implement resilience mechanisms such as circuit breakers, manual overrides, and Human-in-the-Loop;
• Develop evaluation benchmarks and continuous improvement feedback loops;
• Integrate CI/CD pipelines for automated deployment of agents;
• Integrate platform components with enterprise tools;
• Manage cloud infrastructure and optimize LLM cost and performance.

• Strong proficiency in Python (minimum 3 years) applying SOLID principles and best practices;
• Hands-on experience with Azure Cloud and Azure AI Services;
• Experience with RAG frameworks and ingestion pipelines;
• Knowledge of vector databases;
• Experience with REST APIs and enterprise system integrations;
• Solid understanding of DevOps and MLOps practices;
• Experience with identity and access management;
• Familiarity with observability, monitoring, and performance optimization;
• Strong problem-solving skills and ability to work in distributed teams.

• No conditions specified