Quick Summary
Define AI standards, reference architectures, and reusable design patterns that accelerate consistent, high-quality solution delivery. Design scalable, secure,
Required Experience 8+ years of experience in software engineering, solution architecture, or enterprise application development. 4+ years of experience designing and delivering AI, GenAI,
Responsibilities
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8+ years of experience in software engineering, solution architecture, or enterprise application development.
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4+ years of experience designing and delivering AI, GenAI, intelligent automation, or machine learning solutions.
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Strong experience with Copilot Studio, Microsoft Foundry, Azure OpenAI, and Azure AI Search.
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Strong understanding of Copilot Studio and enterprise AI solution design.
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Solid experience with the Azure platform, including application hosting, integration, security, identity, networking, storage, and data services.
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Proficiency in Python or other programming languages and experience with modern software development practices.
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Experience designing and integrating REST APIs and enterprise applications.
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Hands-on experience with SQL and relational databases.
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Experience with GitHub and source control best practices.
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Strong understanding of LLMs, Generative AI, prompt engineering, vector search, embeddings, and RAG architectures.
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Experience with agent-based architectures, orchestration frameworks, and Human-in-the-Loop solutions.
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Knowledge of AI evaluation methods, quality measurements, monitoring, and observability practices.
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Understanding of Responsible AI, AI governance, and AI cost optimization principles.
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Strong understanding of AI-assisted software development practices, including the effective use of tools such as M365 Copilot, Cursor AI, Claude Code, and similar AI-powered engineering assistants.
You should be comfortable making architecture decisions across:
Low-code vs pro-code approaches.
Copilot Studio vs custom AI solutions.
Single-agent vs multi-agent architectures.
Human-in-the-Loop vs autonomous workflows.
Trade-offs between speed, scalability, security, and cost.
Excellent communication and stakeholder management skills.
Ability to communicate effectively with both technical and business audiences.
Fluent written and spoken English.
Nice To Have:
Power Platform ecosystem knowledge
Azure DevOps and CI/CD pipeline experience.
Microsoft Graph API.
LangChain, LangGraph, AutoGen, Microsoft Agent Framework, or similar frameworks.
Vector databases such as Qdrant or ChromaDB.
Databricks, or Microsoft Fabric.
Containers, Docker, Kubernetes.
Voice AI and conversational AI platforms.
Experience with frameworks such as FastAPI, Spring Boot, Express.js, or similar.
#LI-BS1 #LI-Remote
Location & Eligibility
Listing Details
- First seen
- October 5, 2026
- Last seen
- October 5, 2026
Posting Health
- Days active
- 0
- Repost count
- 0
- Trust Level
- 51%
- Scored at
- October 5, 2026
Signal breakdown
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