GenAI / Applied LLM Engineer

• Develop and deploy GenAI applications using LLMs, RAG pipelines, and prompt engineering techniques

• Build scalable backend services and APIs using Python and C#/.NET for AI workloads

• Implement enterprise AI solutions using Azure OpenAI, Azure AI Foundry, and vector search systems

• Design data ingestion and retrieval pipelines using SQL Server, Cosmos DB, and Azure data services

• Develop frontend interfaces using Angular for internal AI tools and applications

• Fine-tune or adapt LLMs using parameter-efficient tuning methods where applicable

• Integrate AI models into enterprise applications, engineering workflows, and automation systems

• Apply MLOps practices for deployment, monitoring, versioning, and model lifecycle management

• Ensure secure, compliant, and responsible AI implementation aligned with enterprise standards

• Collaborate with data engineers, architects, and SMEs to translate requirements into AI solutions

• Implement observability using tools like App Insights, Prometheus, and OpenTelemetry

• Document AI systems, workflows, and provide training for adoption across teams