AI Engineer (Contract)

The Focus Group; Sandton; On-site; ZAR 900,000 - 2,000,000; Full time

Job summary

The Focus Group is seeking an AI Engineer to design, build, and deploy scalable AI-driven solutions using Copilot Studio and Azure AI Foundry. The role aims to automate business processes, accelerate AI use cases, and boost operational efficiency across the organization.

You will work on agent-based architectures, generative AI, and enterprise data integration while following governance and best practices.

Qualifications

• 1–3 years hands-on experience in Microsoft Copilot Studio and Microsoft Azure AI Foundry.
• Proven experience building and deploying AI/ML or generative AI solutions.
• Experience in agent-based architectures or conversational AI.

Responsibilities

• Design and implement AI-powered agents and copilots using Copilot Studio.
• Develop orchestration pipelines using Azure AI Foundry.
• Build hybrid architectures combining Copilot Studio and Foundry.

Skills

Copilot Studio

Azure AI Foundry

AI/ML solutions

Agent-based architectures

Conversational AI

Tools

GitHub

CI/CD pipelines

DevOps practices

Job description

Job Summary:

The AI Engineer will design, build, and deploy scalable AI-driven solutions using Microsoft Copilot Studio and Azure AI Foundry, with the objective of automating business processes, accelerating delivery of AI use cases, and improving operational efficiency across the business.

The role requires strong engineering capability across agent-based architectures, generative AI, and enterprise data integration, while ensuring adherence to established standards, governance, and best practices.

2. Key Responsibilities

Solution Design & Engineering

• Design and implement AI-powered agents and copilots using Copilot Studio.

• Develop advanced AI solutions and orchestration pipelines using Azure AI Foundry.

• Build hybrid architectures combining Copilot Studio (front-end interaction) and Foundry (backend intelligence).

• Implement multi-step reasoning workflows and agent orchestration for complex use cases.

Data Integration & AI Enablement

• Integrate AI solutions with enterprise systems using:

• APIs, connectors, and microservices

• Data platforms (e.g., enterprise data lakes, SQL, graph DBs)

• Develop and optimise Retrieval-Augmented Generation (RAG) pipelines for enterprise knowledge use cases.

Agent Development & Deployment

• Build and deploy scalable AI agents across business domains.

• Enable multi-channel deployment (e.g., Microsoft Teams, Power Platform).

• Ensure robust testing, validation, and performance optimisation prior to production release.

Governance, Quality & Standards

• Apply best practices across:

• Security (RBAC, managed identities, Key Vault)

• Data governance and compliance

• Responsible AI and risk mitigation

• Conduct peer reviews on solution design and code and guide team adoption of standards.

Performance Optimisation & Monitoring

• Optimise model usage, cost, and response accuracy.

• Implement observability (logging, monitoring, tracing).

• Diagnose and resolve issues across Copilot--Foundry integrations.

Coaching & Enablement

• Mentor squad members and facilitate knowledge transfer.

• Support capability uplift across the AI squad and broader CIB community.

• Contribute to reusable patterns, frameworks, and playbooks.

3. Experience & Qualifications

Mandatory Experience

• 1--3 years hands-on experience in:

• Microsoft Copilot Studio

• Microsoft Azure AI Foundry

• Other AI Tools / Platforms

• Proven experience building and deploying AI/ML or generative AI solutions

• Experience in agent-based architectures or conversational AI

Technical Skills

• Programming:

• Python (preferred), API integration

• AI/LLM capabilities:

• Prompt engineering

• RAG pipelines

• Model evaluation and tuning

• Cloud & Data:

• Microsoft Azure ecosystem

• Data integration (SQL, APIs, data lakes)

• Tooling:

• GitHub, CI/CD pipelines, DevOps practices / SAFe / Agile

5. Key Competencies

• Strong problem-solving and analytical thinking

• Ability to design scalable, production-grade AI solutions

• Excellent communication and stakeholder engagement

• Commitment to quality, governance, and standards

• Continuous learning mindset in emerging AI technologies