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).