AI Engineer Senior Consultant
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Key skills for this role
About the Role
Protiviti Middle East is seeking a Senior Consultant-level AI Engineer to design and build production-grade Agentic AI solutions. You will develop intelligent agents and copilots using Microsoft Copilot Studio, Azure AI Foundry, and Anthropic's Claude, combining hands-on engineering with client-facing consulting.
Key Skills for This Role
Responsibilities
- Build agentic AI use cases: design, develop, and deploy autonomous and semi autonomous agents
- Develop on multiple platforms: Microsoft Copilot Studio, Azure AI Foundry, and Claude via Anthropic API
- Design solution architecture for AI systems including agent orchestration, RAG, memory, guardrails
- Engineer prompt and context layer; build evaluation harnesses for quality, safety, and reliability
- Integrate agents with enterprise APIs, databases, knowledge bases, and Microsoft 365/Azure services
- Advise clients and internal teams, shape use cases, run proofs of concept, estimate effort, guide junior engineers
- Apply best practices for testing, monitoring, cost control, observability, and responsible AI
Requirements
- 5+ years in software/data/AI engineering
- At least 1 2 years building LLM based or agentic AI applications
- Strong programming skills in Python
- Experience with Microsoft Copilot Studio, Azure AI Foundry, and Anthropic Claude
- Solid understanding of machine learning fundamentals and generative AI concepts
- Excellent communication and stakeholder management skills
- Ability to produce clear architecture diagrams
- Experience with multi agent frameworks (e.g., LangGraph, Semantic Kernel, AutoGen, CrewAI)
- Familiarity with cloud platforms (Azure preferred; AWS/GCP welcome) and DevOps/MLOps practices
- Exposure to responsible AI, governance, and enterprise data security frameworks
- Relevant certifications (e.g., Azure AI Engineer Associate)
Full Job Posting
Role Overview
- We are looking for a Senior Consultant–level AI Engineer to design and build production grade Agentic AI solutions for our clients.
- You will own the end to end development of intelligent agents and copilots — from use case discovery and architecture through to deployment — across Microsoft Copilot Studio, Azure AI Foundry, and Anthropic’s Claude.
- This is a builder’s role with a client facing edge: you will spend most of your time engineering agents, but you will also shape solutions, advise stakeholders, and set the technical direction for delivery teams.
What You’ll Do
- Build agentic AI use cases — design, develop, and deploy autonomous and semi autonomous agents that plan, reason, use tools, and orchestrate multi step workflows.
- Develop on multiple platforms — implement solutions across Microsoft Copilot Studio, Azure AI Foundry, and Claude via the Anthropic API and agent frameworks.
- Design the architecture — define solution architecture for AI systems, including agent orchestration, tool/function calling, RAG, memory, guardrails, and integration.
- Engineer the prompt and context layer — craft and optimize prompts, context strategies, and tool definitions; build evaluation harnesses.
- Integrate with the enterprise — connect agents to APIs, databases, knowledge bases, and Microsoft 365 / Azure services.
- Advise and lead — work directly with clients and internal teams to shape use cases, run proofs of concept, estimate effort, and guide junior engineers.
- Operationalize responsibly — apply best practices for testing, monitoring, cost control, observability, and responsible AI.
What You’ll Bring
- 5+ years in software/data/AI engineering, with at least 1–2 years building LLM based or agentic AI applications.
- Proven, hands on delivery of agentic or copilot solutions in production or advanced proof of concept settings.
- Strong programming skills in Python (comfort with JavaScript/TypeScript or C# is a plus).
- Microsoft Copilot Studio — building agents, topics, actions, connectors, and integrations within the Power Platform ecosystem.
- Azure AI Foundry — deploying and orchestrating models, building RAG pipelines, and using its evaluation and safety tooling.
- Anthropic Claude — developing with the Claude API, tool use / function calling, agent loops, and prompt design.
- Solid understanding of machine learning fundamentals — supervised vs. unsupervised learning, model training and evaluation, embeddings.
- Strong grasp of generative AI concepts — transformers and LLM behavior, RAG, fine tuning vs. prompting trade offs, evaluation, and hallucination mitigation.
- Working knowledge of AI system architecture — agent orchestration patterns, vector stores and retrieval, API and event driven integration, security and identity, scalability.
- Ability to produce clear architecture diagrams and design decisions that non technical stakeholders can follow.
- Excellent communication and stakeholder management skills; comfortable presenting to and advising senior client audiences.
- Ability to scope ambiguous problems, manage delivery, and mentor others.
Nice to Have
- Experience with multi agent frameworks (e.g., LangGraph, Semantic Kernel, AutoGen, CrewAI).
- Familiarity with cloud platforms (Azure preferred; AWS/GCP welcome) and DevOps/MLOps practices.
- Exposure to responsible AI, governance, and enterprise data security frameworks.
- Relevant certifications (e.g., Azure AI Engineer Associate).
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