1 day ago
Bengaluru, IndiaMid Level / Senior
Responsibilities
- Build application-facing AI features powered by LLMs, agentic workflows, and AI orchestration platforms.
- Integrate MLOps-managed agents and LLM capabilities through AI Gateway patterns involving routing, authentication, policy controls, and logging.
- Design and implement agentic workflows using tool calling, function calling, context handling, prompt version management, and orchestration patterns.
- Use A2A frameworks and MCP Protocol to support interoperable agent communication and workflow execution.
- Develop RAG-based solutions using vector embeddings, vector databases, Azure AI Search, Redis, Cosmos DB, and cloud data stores.
- Build and orchestrate LLM-powered applications with 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.
- Implement testing, observability, monitoring, evaluations, guardrails, safety controls, and incident support for production readiness.
- Partner with security, compliance, architecture, and platform teams on governance, data protection, and enterprise controls.
- Document integration patterns, architecture, operational runbooks, evaluation practices, and reusable engineering components.
Requirements
- 4-8 years of experience.
- Bachelor of Engineering, Bachelor of Technology, Master of Engineering, Master of Technology, or MCA qualification; the posting specifically lists Master of Engineering and Bachelor of Engineering as required fields of study.
- Experience building production AI integrations using LLMs, agents, orchestration frameworks, and APIs.
- Hands-on experience with Agentic AI, A2A frameworks, MCP Protocol, tool and function calling, and workflow orchestration.
- Expertise in vector embeddings, prompt engineering, prompt versioning, context engineering, and RAG.
- Experience with LangChain and LangGraph.
- Strong Python skills plus at least one backend language such as Java or Node.js.
- Proficiency deploying on Azure Cloud, including experience with Azure Functions and Azure Container Apps.
- Experience with Azure AI Search, vector databases, Redis, Cosmos DB, and related data platforms.
- Strong software engineering fundamentals in testing, observability, reliability, secure integration, and production support.
- Familiarity with evaluation methods, guardrails, monitoring, and safety or quality controls.
- Understanding of cloud-native architecture, scalability, and performance optimization.
- Strong interpersonal and negotiation skills.
- Preferred experience includes Blob Storage, Iceberg, Kubernetes, Docker, CI/CD, MLOps pipelines, Azure AI Foundry, Azure OpenAI, AWS AI services, multi-cloud AI platforms, enterprise AI Gateway patterns, policy enforcement, GenAI governance, reusable AI engineering assets, responsible AI, data privacy, compliance, and secure enterprise AI delivery.
Benefits
- PwC states that it offers inclusive benefits, flexibility programmes, mentorship, wellbeing support, and opportunities for learning and growth.
- The role is based in Bangalore, India.
- The posting states that work visa sponsorship is not available.
- The job posting end date is April 15, 2026.
Categories
About PwC
PwC is a global network of professional services firms providing assurance, tax, and advisory work for businesses and public-sector clients. It sells project-based and managed consulting, audit, and deals services, and implements and integrates business applications. Formed in 1998 by the merger of Price Waterhouse and Coopers & Lybrand, it is headquartered in London and is one of the Big Four accounting firms.