AI Agent

Role Overview

The AI Agent & Automation Engineer is responsible for designing, building, and deploying enterprise-grade AI agent systems that combine low-code platforms with custom development where needed. This role requires hands-on experience with Microsoft Copilot Studio and/or Agentforce 2dx, a solid understanding of the Azure ecosystem, and practical knowledge of Retrieval-Augmented Generation (RAG) techniques for building vectorized semantic layers. While the primary focus is on low-code development, the engineer must also be proficient in Python and prepared to adopt emerging AI agent orchestration frameworks as the AITO evolves..

Key Responsibilities

• Design and implement AI agent solutions using Power Automate/Microsoft Copilot Studio and/or Agentforce 2dx.
• Integrate AI agents with business systems and data sources within the Azure ecosystem.
• Full understanding of Azure AI Foundry, RAG architecture and development of semantic and cognitive data layers
• Collaborate with wider team to understand requirements and translate them into technical solutions.
• Participate in Agile ceremonies and contribute to sprint planning and delivery.
• Ensure scalability, maintainability, and performance of AI agent systems.
• Continuously explore and adopt new AI agent orchestration technologies.
• Design and maintain vectorized semantic layers (indexes, embeddings, hybrid retrieval) to support AI agent grounding and enterprise search.
• Own the IndexOps lifecycle: ingestion/chunking versioning, re‑embedding strategies, relevance tuning, freshness SLAs, and search security trimming.

Essential Skills & Experience

• Hands-on experience with Power Automate and/or Microsoft Copilot Studio/ and or Agentforce 2dx.
• Strong understanding of the Azure ecosystem and its AI services.
• Proficiency in Python and ability to write clean, maintainable code.
• Experience in low-code/no-code development environments.
• Ability to work in Agile teams and deliver high-quality technical solutions.
• Deployment with Azure AI Agent Service or Copilot Studio SaaS runtime.
• Experience implementing RAG pipelines, including vectorized indexing (Azure AI Search or equivalent), embedding generation, and relevance tuning.
• Experience with AI evaluation and safety (e.g., Prompt flow test gates, groundedness checks, Azure AI Content Safety policies) for quality, compliance, and cost control.
• Enterprise security & networking on Azure (Microsoft Entra ID/RBAC, private networking/VNet, BYO storage/search/thread stores) and data residency controls.

Desirable Skills

• Experience with automation/AI orchestration frameworks or multi-agent systems.
• Familiarity with orchestration frameworks (e.g., Semantic Kernel) or willingness to rapidly learn.
• Knowledge of REST APIs and integration patterns.
• Familiarity with DevOps practices and CI/CD pipelines.
• Understanding of vector database concepts, hybrid retrieval strategies, and security trimming for enterprise search
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• Experience with embedding model selection, chunking strategies, and evaluation of retrieval quality (e.g., Prompt flow or equivalent).

Personal Skills and Attributes

• Strong communication and interpersonal skills.
• Excellent planning and reasoning abilities.
• Ability to work under pressure and in ambiguous situations.
• Creative and resilient mindset.
• Strong focus on delivery and quality.
• Motivated by the opportunity and challenge of contributing to SCC's AI journey.

Interplay with Pod Roles

• Collaborates with the AITO team to understand business requirements.
• Works with the team to ensure smooth deployment and adoption.
• Engages with the local market AI Product Owner to align on technical feasibility and delivery timelines.
• Supports cross-functional collaboration within the pod to ensure cohesive delivery.