Job Description
We are seeking an experienced AI Manager with deep expertise in Azure AI, Microsoft Fabric, and Machine Learning ecosystems to design and implement enterprise-grade AI solutions
.The ideal candidate combines strong technical leadership with hands-on experience architecting end-to-end AI/ML systemsfrom data readiness through model deploymentleveraging Azure's cloud-native and Fabric-based services
.
Key Responsibiliti
- esArchitect and lead the design and implementation of AI/ML solutions on Azure Cloud (Azure Machine Learning, Azure Databricks, Synapse, Azure AI Foundry, Microsoft Fabric, Cognitive Services, Azure OpenAI etc.
- ).Define end-to-end AI architecture encompassing data pipelines, feature stores, model training, deployment, and monitorin
- g.Partner with stakeholders to translate business challenges into AI-driven solutions and technical blueprint
- s.Design scalable and secure architectures adhering to best practices in data governance, MLOps, LLMOps, and cost optimizatio
- n.Integrate Microsoft Fabric as the unified data foundation for AI workloads, ensuring governed, high-quality data access and lineage visibilit
- y.Lead MLOps initiatives including model CI/CD, versioning, monitoring, and drift detection using Azure DevOps, Azure ML Pipelines, and Azure AI Foundr
- y.Evaluate and implement Generative AI (GenAI) and LLM-based solutions using Azure OpenAI, Cognitive Services, and frameworks such as LangChain or LangGrap
- h.Establish observability and monitoring frameworks using Azure Monitor, Application Insights, MLflow, and Databricks dashboards for AI workload
- s.Collaborate with cross-functional teamsData Engineers, Data Scientists, and DevOpsto ensure seamless integration and delivery of AI product
- s.Provide technical mentorship and architectural guidance to engineering team
- s.Stay current with emerging trends in AI/ML, cloud technologies, and GenAI advancement
s.
Qualificati
- ons8+ years of overall IT experience, including 4+ years in AI/ML solutioning and 3 + years in Azure-based architectu
- re.Deep expertise in the Azure AI ecosystemAzure Machine Learning, Azure Databricks, Azure AI Foundry, Microsoft Fabric, Azure Cognitive Services, Azure OpenAI, Azure Synapse, and Data La
- ke.Strong proficiency in Python and major ML frameworks (PyTorch, TensorFlow, Scikit-lear
- n).Proven experience with transformer model architectures and practical understanding of LLM specifics like context handli
- ng.Proven experience designing, implementing, and optimising prompt strategies (e.g., chaining, templates, dynamic inputs); practical understanding of output post-processi
- ng.Must have hands-on experience implementing and automating MLOps/LLMOps practices, including model tracking, versioning, deployment, monitoring (latency, cost, throughput, reliability), logging, and retraining workflo
- ws.Must have worked extensively with MLOps/experiment tracking and operational tools (e.g., MLflow, Weights & Biases) and have a demonstrable track reco
- rd.Proven ability to monitor, evaluate, and optimise AI/LLM solutions for performance (latency, throughput, reliability), accuracy, and cost in production environmen
- ts.Proven experience in MLOps and LLMOps design and automation using Azure DevOps, Docker, and Kubernet
- es.Hands-on experience integrating AI solutions with Microsoft Fabric and Azure Data Factory for data preparation and governan
- ce.Strong understanding of distributed systems, model lifecycle management, and AI system scalabili
- ty.Experience in LLM fine-tuning, prompt engineering, or AI solution integration with enterprise applicatio
- ns.Excellent communication and stakeholder management skills with a strategic minds
et.
