Artificial Intelligence Consultant

Microvision is hiring a hands-on AI Engineer who loves building, experimenting, and shipping AI solutions.

This role is ideal for someone who has already built AI prototypes, internal tools, or production features—whether through work, side projects, hackathons, or startups—and now wants to apply those skills to real-world public sector and enterprise challenges.

You will work closely with product..., engineering, and solution teams to create LLM-powered applications, RAG-based systems, and AI-enabled workflows using Microsoft's AI ecosystem.

This is a doer role, not a research-only position.

What You'll Work On

AI copilots for inspections, compliance, and case management

RAG-based systems over policies, regulations, and operational data

AI-powered workflows embedded into Power Apps and Power Automate

Prototypes that move quickly from idea → demo → pilot → production

Key Responsibilities

Build & Ship AI Solutions

Develop LLM-powered applications using Azure OpenAI

Implement Retrieval-Augmented Generation (RAG) pipelines

Build APIs and backend services in Python to support AI features

Create proof-of-concepts and iterate rapidly based on feedback

Microsoft Stack & Low-Code Integration

Embed AI capabilities into:

Power Apps (Canvas / Model-driven exposure)

Power Automate workflows

Integrate AI outputs into dashboards, forms, and operational tools

Collaborate with solution architects to align with enterprise standards

Applied AI Engineering

Work with embeddings, vector search, and document ingestion pipelines

Apply prompt engineering and evaluation techniques

Assist in deploying AI workloads on Azure (Functions, App Services, Containers)

Innovation & Collaboration

Contribute ideas during innovation workshops and sprints

Document learnings, patterns, and reusable components

Support demos and pilots for government and enterprise stakeholders

Required Qualifications (Hands-On Focus)

We care more about what you've built than how long you've worked.

Must-Have Skills

Practical experience with LLMs (OpenAI / Azure OpenAI / similar)

Hands-on exposure to RAG architectures

Proficiency in Python

Familiarity with Microsoft Azure and cloud-based deployments

Basic exposure to Power Apps and/or Power Automate (building or extending apps)

Strongly Preferred (But Not Mandatory)

Chatbots, copilots, AI assistants

Document intelligence or search systems

Experience with tools such as: LangChain, Semantic Kernel, LlamaIndex

Familiarity with vector databases or search services

Exposure to REST APIs, authentication, and secure integrations

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