Senior AI Systems & Applications Engineer

It's fun to work in a company where people truly BELIEVE in what they're doing!

We're committed to bringing passion and customer focus to the business.

SUMMARY:

We are seeking a versatile AI Solutions Architect to lead the design and implementation of our next-generation agentic AI ecosystem. You will bridge the gap between data engineering and application development, leveraging the full Microsoft Azure AI Foundry (formerly AI Studio) and MS Fabric suite.

The ideal candidate doesn't just "call an API"; they architect secure, governed, and multi-agentic systems that integrate deeply with enterprise data via One Lake and stay protected through MS Purview. You will be responsible for building the "connective tissue" of our AI strategy—from MCP server integration to complex prompt orchestration.

DUTIES AND RESPONSIBILITIES:

AI Orchestration:
Design and deploy agentic and multi-agentic workflows using Azure AI Foundry, Semantic Kernel, or Auto Gen.

Data Strategy:
Architect and manage data pipelines within MS Fabric One Lake, ensuring "Gold" layer data is ready for RAG (Retrieval-Augmented Generation) and model fine-tuning.

Security & Identity:
Execute application and agent registration via MS Entra (formerly Azure AD), implementing OAuth flows and Managed Identities for secure tool access.

Governance:
Configure and maintain MS Purview to ensure data lineage, sensitivity labeling, and AI safety guardrails are enforced across all LLM interactions.

Connectivity:
Build and maintain MCP (Model Context Protocol) servers and custom tools to allow AI agents to interact securely with internal databases and third-party SaaS.Development:
Build production-ready application interfaces (React/Next.js or Python-based frameworks) that integrate seamlessly with backend AI flows.

REQUIRED TECHNICAL

SKILLS:

Microsoft AI & Data Stack Azure AI Foundry / MS Foundry:
Deep expertise in Prompt Flow, model evaluation, and deployment of GPT-4o/o1 and SLMs (Phi-3).MS Fabric & One Lake:

Experience with Lake houses, Shortcuts, and integrating Fabric data with AI search indexes.

MS Purview:
Implementation of data loss prevention (DLP) and sensitivity labels within AI-generated content.

MS Entra:
Advanced knowledge of App Registrations, Service Principals, and Scopes for AI Agents.

Generative & Agentic AIPrompt Engineering:
Advanced techniques (Chain-of-Thought, ReAct, Few-shot) and prompt versioning.

Agentic Frameworks:
Proficiency in building autonomous agents that can use tools, manage state, and collaborate (multi-agentic patterns).MCP (Model Context Protocol):
Experience implementing MCP servers to standardize how LLMs access local and remote data.

Software Engineering

Languages:

Python (FastAPI/Lang Chain/Semantic Kernel) and Type Script/C#.Tooling:
Expert-level use of VS Code / Cursor, Git Hub Copilot, and Azure Dev Ops for CI/CD.

Infrastructure: Infrastructure-as-Code (Bicep or Terraform) for deploying AI workloads.

Experience RequirementsB.S./M.S. in Computer Science, Data Science, or a related field.

Certifications Preferred:
Microsoft Certified:
Azure AI Engineer Associate (AI-102) or Microsoft Certified:
Fabric Analytics Engineer Associate (DP-600).5+ years’ experience in Software Development, with at least 2+ years of dedicated focus on Generative AI and LLM integration.

Project History:
Proven track record of moving an AI project from a "notebook" prototype to a governed, production-scale enterprise application.

Security Mindset:
Understanding of the "AI Red Teaming" concept and mitigating risks like prompt injection.

COMPETENCIES:

Ethics
- Treats people with respect;
Keeps commitments;
Inspires the trust of others;
Works with integrity and ethically;
Upholds organizational values.

Adaptability
- Adapts to changes in the work environment;
Manages competing demands;
Changes approach or method to best fit the situation;
Able to deal with frequent change, delays, or unexpected events.

Analytical
- Synthesizes complex or diverse information;
Collects and researches data;
Uses intuition and experience to complement data;
Designs work flows and procedures.

Change Management
- Develops workable implementation plans;
Communicates changes effectively;
Bui…