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Career Family: AIA - Agentic AI Engineer

The opportunity

We are seeking a energetic Senior Consultant to join our AI & Data Consulting team, focused on building enterprise-grade GenAI and Agentic AI solutions with strong emphasis on LLM engineering, frontend experience layer, reusable UI components, and real-time copilot interfaces.

The ideal candidate will bring a strong combination of AI engineering, LLM application development, agentic AI system design, backend engineering, and modern frontend development expertise. This role requires hands-on experience in building chatbots, copilots, agent-driven workflows, reusable UI SDKs, streaming interfaces, and API-driven AI experiences that are scalable, secure, maintainable, and production-ready.

You will work closely with AI engineers, backend engineers, UX designers, product owners, security teams, platform teams, and business stakeholders to design and implement LLM-powered applications, agentic workflows, Retrieval-Augmented Generation (RAG) pipelines, streaming AI interfaces, and reusable experience-layer components that accelerate enterprise AI adoption and business transformation.

Your key responsibilities

Technical Excellence

- AI Engineering & Agentic AI Development
- Design and develop enterprise-grade GenAI and Agentic AI applications using LLM frameworks such as LangChain, LangGraph / AutoGen / Google Agent SDK, and Model Context Protocol (MCP).
- Build agentic AI architectures including multi-agent workflows, tool/function calling, enterprise integrations, memory patterns, and autonomous decision flows.
- Develop and maintain Retrieval-Augmented Generation (RAG) pipelines including document ingestion, chunking, embeddings generation, vector indexing, retrieval optimization, and response grounding.
- Implement semantic search and knowledge retrieval solutions using vector databases and hybrid search patterns.




- Develop prompt engineering strategies, tool-based agents, AI workflows, and enterprise copilots aligned to business use cases.
- Contribute to AI evaluation, observability, monitoring, and performance optimization of LLM-powered applications.
- Stay current with emerging trends in GenAI, Agentic AI, LLM frameworks, AI SDKs, multimodal AI, and enterprise AI engineering practices.

- Frontend & Experience Layer Engineering

- Design and build modern AI user experiences using React, TypeScript, Next.js, reusable UI component libraries, and frontend SDKs.
- Develop chatbot, copilot, and agent-driven interfaces that provide intuitive, responsive, and accessible user experiences.
- Build reusable React and TypeScript components and SDKs that can be consumed across multiple applications and teams.
- Implement state management, client-side performance optimization, accessibility standards, and design system integration for enterprise-grade AI applications.
- Develop API-first and contract-driven UI integrations with backend services, agent APIs, and streaming endpoints.
- Implement extensible plug-in patterns, schema-driven forms, typed API clients, and component-driven architectures for scalable AI experiences.

- Streaming & Real-time UI Development

- Implement real-time AI interfaces using WebSockets, Server-Sent Events (SSE), and token-level LLM response streaming.
- Build streaming chat, copilot, and agent interfaces with incremental rendering, backpressure handling, and low-latency response patterns.
- Develop real-time visualization of agent state, workflow progress, tool usage, and execution traces.
- Optimize streaming performance across frontend, backend, and LLM service layers.
- Ensure safe rendering of model output, including UI-level guardrails, content handling, and secure display patterns.





- Backend & Platform Engineering

- Design and build scalable backend services using Python, FastAPI, REST APIs, microservices, and event-driven architectures.
- Develop reusable AI platform components, services, APIs, and integrations to accelerate enterprise AI adoption.
- Integrate AI solutions with enterprise systems, third-party applications, workflow platforms, and data services.
- Troubleshoot and optimize AI pipelines, APIs, vector stores, backend services, and cloud-native applications.
- Implement scalable deployment strategies using containerized and cloud-native architectures.

- Cloud, Infrastructure & DevOps

- Deploy and manage AI applications using Docker, Kubernetes, OpenShift, and cloud-native deployment patterns.
- Build and maintain CI/CD pipelines using GitHub Actions, GitLab CI, and modern DevOps tooling.
- Ensure production readiness through monitoring, observability, automated testing, release management, and operational excellence.
- Support deployment and lifecycle management across development, testing, staging, and production environments.
- Apply scalable deployment patterns for AI services, frontend applications, reusable SDKs, and backend platforms.

- AI Governance, Security & Responsible AI

- Implement controls for PII protection, data privacy, AI security, compliance, and responsible AI practices.
- Support AI governance through monitoring, observability, auditability, access controls, and policy-aligned implementation.
- Apply guardrails for prompt injection mitigation, safe tool execution, secure API access, and safe rendering of model output in UI experiences.
- Contribute to AI observability practices including monitoring model behavior, hallucination risks, agent trajectories, retrieval quality, latency, accuracy, and user experience performance.
- Ensure adherence to enterprise architecture, information security, accessibility, responsible AI, and engineering standards.

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

📌 EY - GDS Consulting - AIA - Agentic AI Engineer- Senior (Bengaluru)
🏢 EY
📍 Bengaluru