Job Description
<p><p><b>Key Responsibilities :</b></p><p><br/>- Architect and implement intelligent applications using Azure AI services including Azure OpenAI, Azure Cognitive Services, and Azure Machine Learning.<br/></p><p><br/></p><p>- Lead AI experimentation initiatives to evaluate models, configurations, and deployment strategies aligned with business goals.<br/></p><p><br/></p><p>- Embed AI capabilities such as NLP, computer vision, speech recognition, and decision-making into enterprise applications.<br/></p><p><br/></p><p>- Integrate AI models with internal and external systems (web, mobile, APIs) ensuring seamless interaction with business logic.<br/></p><p><br/></p><p>- Design and implement scalable, low-latency, and high-availability AI components using Azure App Services, AKS, and serverless patterns.<br/></p><p><br/></p><p>- Provision and manage Azure AI Foundry workspaces, compute environments, and model endpoints.<br/></p><p><br/></p><p>- Implement secure access controls, RBAC, and data governance policies to ensure compliance and responsible AI practices.<br/></p><p><br/></p><p>- Guide development teams on MLOps best practices including model versioning, CI/CD pipelines, monitoring, and drift detection.<br/></p><p><br/></p><p>- Collaborate with business stakeholders to identify opportunities for AI-led process optimization and transformation.<br/></p><p><br/></p><p>- Contribute to internal AI strategy committees and innovation forums to shape enterprise AI adoption.<br/></p><p><br/></p><p>- Document architecture patterns, reusable components, and integration blueprints for AI applications.<br/></p><p><br/></p><p>- Actively participate in hands-on coding and development of AI Skills :</b></p><p><br/></p><p>Azure AI & ML :</p><p><br/></p><p>- Azure AI Foundry : Workspace provisioning, model lifecycle management<br/></p><p><br/></p><p>- Azure OpenAI : Prompt engineering, model fine-tuning, endpoint management<br/></p><p><br/></p><p>- Azure Cognitive Services : Vision, Speech, Language, and Decision APIs<br/></p><p><br/></p><p>- Azure Machine Learning : Training, deployment, monitoring, and MLOps<br/></p><p><br/></p><p>- Experience with LLM orchestration and prompt chaining<br/></p><p><br/></p><p>- Familiarity with Azure AI Studio and Azure Arc<br/></p><p><br/></p><p>- Proficiency in using Azure AI SDKs within custom applications<br/></p><p><br/></p><p>- Hands-on experience in at least one AI/ML domain (Computer Vision, Automation, Predictive Analytics, RPA, etc.) with relevant </p><p>libraries (Pandas, TensorFlow, Scikit-learn, etc.)<br/></p><p><br/></p><p>Application Integration :</p><p><br/></p><p>- Programming : Python, .NET, Integration : REST APIs, Azure Functions, Logic Apps, Event Grid<br/></p><p><br/></p><p>- Architecture : Microservices, serverless, event-driven, real-time & batch inference pipelines<br/></p><p><br/></p><p>- Infrastructure : Azure App Services, AKS, API Management<br/></p><p><br/></p><p>- Experience with containerized AI workloads (Docker, & Governance :</p><p><br/></p><p>- RBAC, Managed Identities, Private Endpoints<br/></p><p><br/></p><p>- Data privacy, encryption, and responsible AI Skills :</b></p><p><br/></p><p>- Exposure to multi-cloud AI deployment strategies.<br/></p><p><br/></p><p>- Knowledge of AI-driven business process automation and Agentic AI Skills :</b></p><p><br/></p><p>- Strong analytical and problem-solving mindset.<br/></p><p><br/></p><p>- Proactive, self-managed, and Excellent communication and stakeholder engagement skills.<br/></p><p><br/></p><p>- Team player with mentoring and leadership capabilities.<br/></p><p><br/></p><p>- Curious, innovative, and eager to learn and share knowledge.<br/></p><p><br/></p><p>- Strong project tracking and execution :</b></p><p><br/></p><p>- Bachelors or Masters degree in Computer Science, IT, or Data Science.<br/></p><p><br/></p><p>- Preferred : Engineering/Science graduate with specialization in AI/ML.<br/></p><p><br/></p><p>- Mandatory Certification : Microsoft Certified : Azure AI Engineer Associate and/or Azure Solutions Architect :</b></p><p><br/></p><p>- Enterprise-grade intelligent applications powered by Azure AI.<br/></p><p><br/></p><p>- Architecture patterns, reusable AI components, and integration blueprints.<br/></p><p><br/></p><p>- Documented best practices for MLOps and AI governance.<br/></p><p><br/></p><p>- AI-led process transformation roadmaps and strategy Process :</b></p><p><br/></p><p>- Scenario-based technical discussions.<br/></p><p><br/></p><p>- Hands-on assignment (to be submitted within the given timeline).</p><br/></p> (ref:hirist.tech)