Generative AI Developer Data Modeling

Job description

<p><p><b>Description : </b></p><br/><p><b>Job Title : </b> Gen - AI Developer</p><br/><p><b>Experience : </b> 4- 6 Years</p><br/><p><b>Role Overview : </b></p><br/><p>We are looking for an experienced Gen-AI Developer with a strong background in C#, Semantic Kernel, and Azure AI services to design, build, and deploy next-generation AI applications leveraging Large Language Models (LLMs), Agentic AI, and MLOps practices.</p><br/><p>The ideal candidate should bring a mix of hands-on development, infrastructure management, and AI orchestration expertise to create scalable, secure, and cost-optimized Gen AI solutions.</p><br/><p><b>Key Responsibilities : </b></p><br/><p><b>AI Application Development : </b></p><br/><p>- Design, develop, and optimize LLM-powered applications using C#, Semantic Kernel, and .NET Aspire.</p><br/><p>- Implement AI agent architectures for conversational AI, decision-making, and automation workflows.</p><br/><p>- Build custom pipelines for model training, fine-tuning, and deployment (LLMs, NLP, ML).</p><br/><p><b>Cloud & Infrastructure : </b></p><br/><p>- Deploy AI solutions using Azure Services (App Services, AI Foundry, Bot Services, AI Search, Containers).</p><br/><p>- Set up end-to-end environments (Dev/Test/Prod) for ML/LLM/Agentic AI workloads.</p><br/><p>- Implement serverless, containerized, and Kubernetes-based deployments for scalable AI applications.</p><br/><p>- Use Infrastructure as Code (Terraform, ARM templates) for cloud provisioning and automation.</p><br/><p><b>Data Engineering & Pipelines : </b></p><br/><p>- Build ETL/data processing workflows using Apache Airflow, Kafka, Azure Data Factory.</p><br/><p>- Integrate SQL/NoSQL, Data Lakes, and Data Warehouses into AI-driven applications.</p><br/><p>- Manage data pipelines ensuring real-time ingestion, storage, and transformation.</p><br/><p><b>MLOps & CI/CD : </b></p><br/><p>- Establish MLOps frameworks (Kubeflow, MLflow, TFX) for training, deployment, and monitoring of ML/LLM models.</p><br/><p>- Implement CI/CD pipelines (Azure DevOps, GitHub Actions, Jenkins) for AI models and services.</p><br/><p>- Automate testing, monitoring, and retraining cycles to ensure continuous model improvement.</p><br/><p><b>Optimization & Cost Management : </b></p><br/><p>- Monitor and optimize cloud resource utilization to ensure cost efficiency and scalability.</p><br/><p>- Implement auto-scaling strategies for AI workloads.</p><br/><p>- Fine-tune large-scale models for performance and efficiency (latency, throughput, GPU/TPU usage).</p><br/><p><b>Security & Compliance : </b></p><br/><p>- Apply cloud security best practices (IAM, firewalls, VPCs, encryption).</p><br/><p>- Ensure data privacy, secure access, and regulatory compliance in AI & Delivery : </b></p><br/><p>- Work in Agile environments (Scrum/Kanban) with cross-functional teams.</p><br/><p>- Translate business needs into scalable Gen-AI solutions.</p><br/><p>- Communicate complex AI concepts to both technical and non-technical stakeholders.</p><br/><p><b>Technical Skills & Requirements : </b></p><br/><p><b>Programming & AI Development : </b></p><br/><p>- Strong C# and .NET experience (Mandatory).</p><br/><p>- Hands-on with Semantic Kernel for AI orchestration.</p><br/><p>- Expertise in LLM & Gen AI development.</p><br/><p>- Familiarity with Agentic AI frameworks and autonomous agents.</p><br/><p><b>Cloud & Infrastructure : </b></p><br/><p>- Proficiency in Azure AI services (App Services, AI Foundry, AI Search, Bot Services, Containers).</p><br/><p>- Experience with Kubernetes, Docker, serverless architectures.</p><br/><p>- IaC tools : Terraform, ARM templates.</p><br/><p><b>AI/ML & Data Engineering : </b></p><br/><p>- Strong experience in ML, NLP, and LLM development.</p><br/><p>- Familiar with MLOps pipelines (Kubeflow, MLflow, TFX).</p><br/><p>- Data pipeline tools : Apache Airflow, Kafka, Azure Data Factory.</p><br/><p>- Databases : SQL, NoSQL, Data Lakes, Warehouses.</p><br/><p><b>Deployment & Optimization : </b></p><br/><p>- Experience with custom model training, fine-tuning, and inference optimization.</p><br/><p>- Knowledge of GPU/TPU environments, distributed model training.</p><br/><p>- Performance tuning & cost management for cloud-based AI workloads.</p><br/><p><b>Security & Compliance : </b></p><br/><p>- Deep understanding of cloud security frameworks, IAM, encryption.</p><br/><p>- Best practices in secure AI architecture and data governance.</p><br/><p><b>Other : </b></p><br/><p>- Strong problem-solving and debugging skills.</p><br/><p>- Excellent written and verbal communication skills.</p><br/><p>- Ability to work in fast-paced, cross-functional teams.</p><br/><p><b>Preferred Qualifications : </b></p><br/><p>- Experience with local LLM deployments and custom fine-tuning.</p><br/><p>- Exposure to open-source AI orchestration frameworks.</p><br/><p>- Certifications in Azure AI, Cloud Security, or MLOps.</p><br/><p>- Hands-on with AI product lifecycle management from POC ?

Production</p><br/></p> (ref:hirist.tech)

Required Skill Profession

Computer Occupations