Gen AI Engineer With Azure DevOps

JD: As an Gen AI Engineer, you will be a part of an Agile team to build healthcare applications and implement new features while adhering to the best coding development standards .

Responsibilities: -

• Azure Devops
• AKS, Azure Container, Azure mOnitor, LLM, Langsmith
• RAG Pipeline, AgenticAI
• Design, implement, and manage CI/CD pipelines for GenAI applications using Azure DevOps, GitHub Actions, or similar tools.
• Automate infrastructure provisioning using Infrastructure as Code (IaC) tools like Terraform, Bicep, or ARM templates.
• Deploy and manage containerized AI workloads using Azure Kubernetes Service (AKS), Azure Container Apps, or Azure ML.
• Monitor and optimize performance of GenAI applications using tools like Azure Monitor, Application Insights, and LangSmith.
• Implement robust security and compliance practices for AI workloads, including identity management, data encryption, and network security.
• Collaborate with AI/ML engineers and solution architects to ensure smooth integration and deployment of LLMs, RAG pipelines, and agentic workflows.
• Manage Azure resources such as Azure Blob Storage, Azure Cognitive Search, Azure OpenAI, and Azure Key Vault.
• Support model versioning, deployment, and rollback strategies for LLMs and fine-tuned models.
• 7-12 years of relevant experience
• Bachelor's and/or master’s degree in computer science or equivalent experience.
• Strong communication, analytical and problem-solving skills with a high attention to detail.

Skills: -

Mandatory skills

• Gen AI Application engineering using RAG, Agents, Agentic AI and Monitoring Dashboards (LangSmith/LangGraph experience a plus)
• Experience with LLMs (e.g., Open AI, GPT, LLaMA, Claude) deployments and fine-tuning techniques.
• Prompt Engineering -Designing effective prompts for LLMs. Understanding of few-shot, zero-shot, and chain-of-thought prompting.
• Experience with vector databases (Chroma, Pinecone, FAISS etc) and deploying RAG pipelines and CI/CD
• Applied experience in cloud development - Azure, AWS or GCP Cloud.

Good to have skills: -

• Experience with LangChain, LangSmith, or similar GenAI frameworks.
• Knowledge of LLM deployment patterns, including model hosting, inference optimization, and scaling.
• Familiarity with Azure OpenAI Service, Azure ML, and vector databases.
• Exposure to multi-cloud or hybrid cloud environments