Senior AI Application Engineer

Analog Devices•Wilmington, MA

7d•Onsite

About The Position

As a Senior AI Application Engineer, you will be the primary technical builder for ADI's Enterprise AI Productivity program, shaping how our employees work with AI. You will design and ship Copilot Studio agents and Power Automate workflows that employees interact with daily, while building the custom LLM pipelines and RAG architectures that power them with ADI's proprietary knowledge, all within a governed, enterprise-grade architecture. This is a hands-on individual contributor role reporting directly to the Enterprise Productivity Lead, with high visibility across executive stakeholders and cross-functional teams.

Requirements

Copilot Studio - agent design, topics, actions, generative answers, production deployment
Power Automate - cloud flows, HTTP connectors, custom connectors, approval workflows
Microsoft Graph API - querying SharePoint, users, calendar, and Teams data at enterprise scale
Azure Entra ID - app registrations, service principals, OAuth, enterprise permission management
Python (production-grade) - LLM API calls, data pipelines, REST endpoint development
RAG architecture - chunking, embedding, vector stores (Azure AI Search, Pinecone, pgvector, or equivalent)
Azure OpenAI or equivalent LLM API - custom backend integration via Copilot Studio connectors
Power Platform ALM & DLP administration - solution lifecycle, environment strategy, connector governance
Strong collaboration and communication skills across technical and business teams

Nice To Haves

Bachelor's or Master's in Computer Science, Information Systems, AI, or related field
4–7 years in AI engineering, enterprise automation, or Microsoft 365 development (or equivalent project portfolio)
At least one production deployment connecting a Microsoft front-end to a custom LLM or RAG backend
Experience navigating enterprise IT governance — DLP, environment strategy, admin boundaries — in organizations of +50000 employees
Preferred: Azure AI Foundry, LangChain or LlamaIndex, Dataverse schema design, prompt engineering, LLM evaluation
Preferred: PL-200 or PL-400 certification

Responsibilities

Design and ship Copilot Studio agents end-to-end — topic architecture, knowledge grounding, connector integration, and production deployment
Build Power Automate cloud flows connecting agents to SharePoint, Microsoft Graph, Dataverse, and internal APIs
Own the Microsoft Graph API and Azure Entra ID integration layer — service principals, OAuth, and enterprise data access permissions in collaboration with IT
Design and build RAG pipelines grounding agents in ADI's engineering documentation, datasheets, and simulation data using Azure AI Search or equivalent vector stores
Expose custom LLM backends (Azure OpenAI, Claude API, or similar) as REST endpoints callable from Copilot Studio via custom connectors
Establish reusable patterns, component libraries, and ALM practices — managed solutions, environment-to-environment deployment, and CI/CD pipelines — enabling citizen developers to build safely at scale
Instrument agents for usage analytics — adoption metrics, time-saved estimates, and business impact data
Manage Power Platform environment governance — DLP policies, solution lifecycle, environment strategy, and connector security