Pwc
Ai Engineer
Overview
We are seeking a hands-on AI Engineer to design, build, integrate, and support production-grade AI applications powered by LLMs, agentic workflows, RAG, vector search, AI Gateway integrations, and cloud-native Azure services.
About Pwc
At PwC, our people in data and analytics engineering focus on leveraging advanced technologies and techniques to design and develop robust data solutions for clients. They play a crucial role in transforming raw data into actionable insights, enabling informed decision-making and driving business growth.
Requirements & Eligibility
- Experience building production AI integrations using LLMs, agents, orchestration frameworks, and APIs.
- Hands-on experience with Agentic AI, A2A frameworks, MCP Protocol, tool/function calling, and workflow orchestration.
- Strong expertise in vector embeddings, prompt engineering, prompt versioning, context engineering, and RAG.
- Experience with LangChain and LangGraph.
- Strong programming skills in Python and at least one backend language such as Java or Node.js.
- Proficiency in Azure Cloud deployment.
- Experience with Azure AI Search, vector databases, Redis, Cosmos DB, and related data platforms.
- Proven ability to design and manage Azure Functions and Azure Container Apps.
Key Responsibilities
- Build application-facing AI features powered by LLMs, agentic workflows, and AI orchestration platforms.
- Integrate with MLOps-managed agents and consume LLM capabilities through AI Gateway patterns including routing, authentication, policy controls, and logging.
- Design and implement agentic workflows using tool calling, function calling, context handling, prompt/version management, and orchestration patterns.
- Work with Agentic Layer A2A frameworks and MCP Protocol to enable interoperable agent communication and workflow execution.
- Develop RAG-based solutions using vector embeddings, vector databases, Azure AI Search, Redis, Cosmos DB, and relevant cloud data stores.
- Build and orchestrate LLM-powered applications using LangChain, LangGraph, and related frameworks.
- Deploy scalable AI solutions on Azure using Azure Functions, Azure Container Apps, and cloud-native architecture patterns.
- Optimize AI applications for latency, scalability, reliability, cost, and performance.
Disclaimer: Trace Hiring is an independent job board. We are not directly affiliated with Pwc. Please verify all details on the official company application portal.