Description

You will design, implement, and manage GenAI applications and agentic workflows within an Agile healthcare environment.

Responsibilities

• Build and manage CI/CD pipelines for GenAI applications using Azure DevOps or GitHub Actions.
• Automate infrastructure provisioning using 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 GenAI application performance using Azure Monitor, Application Insights, and LangSmith.
• Integrate LLMs, RAG pipelines, and agentic workflows into production environments.
• Manage Azure resources including Azure OpenAI, Azure Blob Storage, Azure Cognitive Search, and Azure Key Vault.

Required Skills

• 7-12 years of relevant experience in software or AI engineering.
• Gen AI application engineering using RAG, Agents, and Agentic AI.
• Experience with LLM deployments and fine-tuning (OpenAI, GPT, LLaMA, Claude).
• Proficiency in Prompt Engineering, including few-shot, zero-shot, and chain-of-thought techniques.
• Experience with vector databases such as Chroma, Pinecone, or FAISS.
• Applied cloud development experience with Azure, AWS, or GCP.
• Hands-on experience with Azure DevOps, Terraform, GitHub Actions, and Azure ML.
• Knowledge of model versioning, deployment, and rollback strategies.
• Degree in Computer Science or equivalent experience.

Preferred Skills

• Experience with LangChain, LangSmith, or LangGraph.
• Knowledge of LLM deployment patterns, inference optimization, and scaling.

Key Skills

Education

Any Graduate