AI Engineer / Cloud Solutions Architect / LLM & Automation Specialist

EDS - Supervising Associate - GEN AI

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AI Engineer / Cloud Solutions Architect / LLM & Automation Specialist

 

Overview

 

We’re seeking an experienced AI Engineer / Cloud Solutions Architect / LLM & Automation Specialist with 8–10 years of overall IT experience, including 5+ years in AI/ML and 3+ years in GenAI & LLM-based system development.

 

This role is ideal for someone who thrives at the intersection of AI innovation, cloud architecture, and intelligent automation, and is passionate about bringing cutting-edge AI solutions into real-world enterprise environments.

 

As part of our advanced engineering team, you will design, architect, and deliver scalable AI agents, multi-agent systems, automation frameworks, and cloud-native AI applications that drive measurable business impact.

 

 

Key Responsibilities

 

AI & LLM Engineering

• Architect, develop, and deploy intelligent solutions using Large Language Models (LLMs) including Azure OpenAI, Google Gemini, and custom fine tuned models.
• Build production-grade AI agents, multi-agent orchestrations, and intelligent tool-augmented workflows.
• Develop context-aware pipelines using frameworks such as LangChain, LangGraph, Autogen, CrewAI, and Model Context Protocol (MCP).
• Design prompt engineering strategies, retrieval-augmented generation (RAG), vector search, and LLM evaluation frameworks.

 

Cloud Architecture & Engineering

• Architect cloud-native AI deployments on Azure (Functions, App Service, Kubernetes, Databricks, SQL, DevOps CI/CD).
• Design scalable, secure, and cost-optimized cloud solutions aligned with enterprise standards.
• Build containerized AI services using Docker, Kubernetes/KaaS, and distributed compute environments.
• Collaborate with security and infrastructure teams to integrate AI solutions with identity, access, and governance requirements.

 

Automation & Workflow Orchestration

• Create end-to-end automation frameworks powered by AI agents, APIs, and cloud services.
• Build intelligent workflows and prototypes using Microsoft Copilot Studio, Streamlit, and other low code environments.
• Integrate LLM capabilities into business processes, enterprise applications, and data pipelines.

 

End-to-End Delivery

• Drive AI solution lifecycle from experimentation, PoC, MVP through production hardening and monitoring.
• Perform model evaluations, feasibility studies, scalability planning, and cost estimation.
• Work cross-functionally with product, engineering, and business stakeholders to translate problems into intelligent solutions.
• Mentor teams and contribute to AI best practices, architecture patterns, and reusable components.

 

 

Core Skills & Technical Expertise

 

AI, ML & GenAI

• 5+ years’ experience in AI/ML including NLP, deep learning, embeddings, model tuning.
• 3+ years hands on experience with GenAI & LLM ecosystems.

 

Expertise in:

• Azure OpenAI (GPT 4, GPT 4o, custom models)
• Google Gemini, Claude (optional exposure)
• LangChain, LangGraph, Autogen, CrewAI, MCP
• RAG pipelines, vector stores (FAISS, Chroma, Azure AI Search)

 

Programming & Prototyping

• Strong expertise in Python (core libraries, async programming, API integration).
• Fast prototyping using Streamlit, Microsoft Copilot Studio, AI Foundry and REST API frameworks.

 

Cloud & DevOps

• Deep knowledge of Azure services: Functions, App Services, DevOps, Kubernetes, Databricks, Key Vault, Storage.
• Experience deploying scalable AI microservices, containerized apps, and secure API endpoints.
• Understanding of MLOps/AIOps frameworks, CI/CD pipelines, and observability patterns.

 

Automation & Integration

• Experience building agentic workflows, orchestration frameworks, and enterprise automation systems.
• Ability to integrate AI with enterprise apps, databases, APIs, and business workflows.

 

 

Preferred Qualifications

 

• Bachelor’s or master’s degree in computer science, Engineering, AI, or related field.
• Certifications in Azure or equivalent cloud/AI credentials.
• Experience with multi-agent system design, retrieval frameworks, and enterprise RAG.
• Exposure to security, governance, and responsible AI practices.

 

EY | Building a better working world

EY is building a better working world by creating new value for clients, people, society and the planet, while building trust in capital markets.

Enabled by data, AI and advanced technology, EY teams help clients shape the future with confidence and develop answers for the most pressing issues of today and tomorrow.

EY teams work across a full spectrum of services in assurance, consulting, tax, strategy and transactions. Fueled by sector insights, a globally connected, multi-disciplinary network and diverse ecosystem partners, EY teams can provide services in more than 150 countries and territories.

Experience Level

Mid Level