Job Description

We are seeking an experienced AI Engineer who specialises in delivering end-to-end AI solutions using Agentic AI frameworks and Generative AI technologies. This role demands consultative skills, technical expertise, and the ability to identify impactful use cases and articulate business benefits while implementing scalable AI solutions.

Key Responsibilities

Design and implement Agentic AI architectures for enterprise workflows. Integrate Generative AI capabilities (LLMs, multimodal models) into client solutions. Deliver end-to-end AI solutions from ideation to production deployment. Build, fine-tune, and evaluate LLM-based Q&A models using frameworks like AWS Bedrock, LangChain, HuggingFace Transformers, or OpenAI API. Design prompt templates and implement retrieval strategies to increase answer precision and factuality. Assist in creating data pipelines for training and testing, including annotation and evaluation tooling. Collaborate with product managers to translate user requirements into technical features. Participate in error analysis, iterative model improvement, and performance tuning. Document code and workflows clearly; follow best practices for reproducibility and code quality. Engage with clients to identify high-value AI use cases and define business benefits. Conduct workshops and assessments to align AI strategies with organisational goals. Provide thought leadership on AI adoption and emerging trends. Develop reusable frameworks and accelerators for Agentic AI and GenAI. Ensure compliance with AI ethics, security, and governance standards. Mentor junior engineers and guide cross-functional teams. Stay ahead of industry developments in Agentic AI, autonomous agents, and LLM ecosystems. Develop and deploy autonomous agents using Azure AI Agent Service, ensuring state management, memory persistence, and secure tool execution. Orchestrate complex multi-agent workflows to handle tasks requiring planning, reasoning, and tool use. Extend Microsoft 365 Copilot by building custom plugins and declarative agents within Microsoft Copilot Studio to surface enterprise data in Teams and Office apps. Operationalize AI solutions using Microsoft AI Foundry for model catalog management, Prompt Flow evaluation, and lifecycle governance. Architect scalable deployment patterns for agents using Azure Container Apps or Azure Functions, ensuring low-latency responses and cost-effective scaling.

Required Skills

Strong experience in Agentic AI frameworks (e.g., LangGraph, AutoGen, CrewAI). Hands-on expertise with Generative AI (LLMs, prompt engineering, fine-tuning). Proficiency in Python and familiarity with deep learning/NLP libraries (LangChain, PyTorch, TensorFlow, HuggingFace Transformers). Experience with building Q&A systems and retrieval-augmented generation pipelines. Knowledge of vector databases or semantic search concepts. Familiarity with cloud AI platforms (AWS Bedrock, Azure OpenAI, GCP Vertex AI). Knowledge of MLOps practices and deployment pipelines. Ability to articulate business value of AI solutions and drive client conversations. Experience with Git, collaborative development workflows, and cloud infrastructure (AWS, Azure, GCP, Domino). Experience building custom copilots and plugins using Microsoft Copilot Studio and integrating them with Power Platform connectors. Proficiency in deploying AI workloads to Azure Container Apps (ACA), Azure Kubernetes Service (AKS), or serverless functions (Azure Functions) for event-driven agent triggers. Experience implementing RAG using Azure AI Search (vector, semantic, and hybrid search) and OneLake/Microsoft Fabric.

Nice to Have Skills

Certification: Microsoft Certified: Azure AI Engineer Associate or similar specialized training in Azure OpenAI. Experience implementing Azure Managed Identities, Private Endpoints, and Content Safety filters for enterprise-grade agent security. Familiarity with tracing agent thought processes (tracing chains/flows) and monitoring token usage in Azure Monitor/App Insights.

Consultative & Business Skills

Excellent stakeholder management and communication skills. Ability to translate technical concepts into business outcomes. Experience in workshops, solution roadmaps, and executive presentations.

Education & Experience

Bachelor's/Master's in Computer Science, AI/ML, or related discipline (or equivalent experience).


Experience in AI solution delivery and client-facing consulting roles.

Why This Role Matters

Agentic AI and Generative AI are redefining automation and decision-making. This role offers the opportunity to lead transformative projects that combine autonomous agents, LLM-powered Q&A systems, and consultative expertise to deliver measurable business impact.