24 hours ago
Mumbai, IndiaMid Level / Senior
Responsibilities
- Build application-facing AI features using LLMs, agents, agentic workflows, APIs, and AI orchestration platforms.
- Integrate MLOps-managed agents through AI Gateway patterns involving routing, authentication, policy controls, and logging.
- Design agentic workflows using tool calling, function calling, context handling, prompt versioning, and orchestration patterns.
- Use A2A frameworks and MCP Protocol to support interoperable agent communication and workflow execution.
- Develop RAG 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 applications for latency, scalability, reliability, cost, and performance.
- Implement testing, observability, monitoring, evaluations, guardrails, safety controls, and incident support.
- 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
- 4–7 years of professional experience in AI/ML engineering, backend development, or related software engineering work.
- Bachelor of Engineering or B.Tech qualification.
- Production experience building 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.
- Strong expertise in vector embeddings, prompt engineering, prompt versioning, context engineering, and RAG.
- Experience with LangChain and LangGraph.
- Strong Python skills and proficiency in at least one backend language such as Java or Node.js.
- Proficiency in Azure Cloud deployment, including Azure Functions and Azure Container Apps.
- Experience with Azure AI Search, vector databases, Redis, Cosmos DB, and related data platforms.
- Strong software engineering fundamentals covering testing, observability, reliability, secure integration, and production support.
- Familiarity with evaluation methods, guardrails, monitoring, and safety and quality controls.
- Understanding of cloud-native architecture, scalability, and performance optimization.
- Strong interpersonal and negotiation skills.
- Preferred experience with Blob Storage, Iceberg, Kubernetes, Docker, CI/CD, and MLOps pipelines.
- Preferred exposure to Azure AI Foundry, Azure OpenAI, AWS AI services, or multi-cloud AI platforms.
- Preferred experience with enterprise AI Gateway patterns, policy enforcement, GenAI governance, reusable AI starter kits, orchestration templates, evaluation harnesses, or observability frameworks.
- Knowledge of responsible AI, data privacy, compliance, and secure enterprise AI delivery.
Benefits
- PwC provides inclusive benefits, flexibility programmes, mentorship, wellbeing support, and professional growth opportunities.
- The role is based in Mumbai, India, within PwC’s Advisory practice.
- The posting lists October 13, 2026 as the job posting end date.
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.