AI Engineer
Senior Consultant —Agentic AI
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. You will combine hands-on engineering with a consultant's instinct for translating business problems into pragmatic, scalable AI systems.
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 to solve real business problems.
- Develop on multiple platforms — implement solutions across Microsoft Copilot Studio (low-code/pro-code agents and copilots), Azure AI Foundry (model deployment, orchestration, and evaluation), and Claude via the Anthropic API and agent frameworks.
- Design the architecture — define solution architecture for AI systems, including agent orchestration, tool/function calling, retrieval-augmented generation (RAG), memory, guardrails, and integration with enterprise data and applications.
- Engineer the prompt and context layer — craft and optimize prompts, context strategies, and tool definitions; build evaluation harnesses to measure quality, safety, and reliability.
- Integrate with the enterprise — connect agents to APIs, databases, knowledge bases, and Microsoft 365 / Azure services using secure, well-governed patterns.
- 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 throughout the lifecycle.
What You'll Bring
Core Experience
- 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).
Platform Expertise
- 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; familiarity with the Model Context Protocol (MCP) and agentic frameworks is a strong plus.
AI & ML Foundations
- Solid understanding of machine learning fundamentals — supervised vs. unsupervised learning, model training and evaluation, embeddings, and where classical ML fits alongside LLMs.
- Strong grasp of generative AI concepts — transformers and LLM behavior, RAG, fine-tuning vs. prompting trade-offs, evaluation, and hallucination mitigation.
AI Architecture
- Working knowledge of how AI systems are architected — agent orchestration patterns, vector stores and retrieval, API and event-driven integration, security and identity, scalability, and cost/performance trade-offs.
- Ability to produce clear architecture diagrams and design decisions that non-technical stakeholders can follow.
Consulting Skills
- 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).
