AI LLM Engineer
Listed on 2026-08-31
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Software Development
AI Engineer (Applied/Software), Machine Learning/ ML Engineer, Data Engineering
AI LLM Engineer (Finance)
Join us in pioneering breakthroughs in healthcare. For everyone. Everywhere. Sustainably.
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Varian Medical Systems, a Siemens Healthineers company is hiring for an AI LLM Engineer. This role is ideal for experienced engineers specializing in Applied AI, Large Language Models (LLMs), and intelligent automation, with a strong foundation in data platforms such as Snowflake and modern analytics ecosystems like Power BI/Fabric. The position focuses on designing, building, and operationalizing AI driven solutions, including RAG pipelines, enterprise copilots, and agent based automation frameworks, to transform how the Analytics & Reporting team delivers insights and interacts with data.
You will partner with business stakeholders, data engineers, and platform teams to build production grade AI systems that enable natural language interaction, automate complex workflows, and enhance self service analytics s role is well suited for someone evolving from data engineering, ML engineering, or analytics engineering into AI platform ownership, agentic system design, or enterprise GenAI leadership.
* This role is designed to be onsite in Atlanta, Georgia with some remote/hybrid flexibility*
What You will do:AI / LLM Engineering & Agentic Systems
- Design, build, and deploy LLM powered applications using architectures such as Retrieval Augmented Generation (RAG), tool augmented agents, and multi agent workflows
- Develop AI copilots and natural language interfaces over enterprise data platforms (Snowflake, Power BI datasets, Fabric/One Lake)
- Build and orchestrate AI agents using frameworks such as:
- Lang Chain / Lang Graph
- Semantic Kernel
- Microsoft Copilot Studio
- Azure AI Foundry
- Implement context management strategies (embeddings, vector stores, retrieval optimization, chunking, ranking)
- Design tool integrations enabling agents to query data, trigger workflows, and interact with enterprise systems
- Develop evaluation frameworks for prompt performance, answer quality, hallucination mitigation, and reliability
- Collaborate with platform and governance teams to ensure responsible AI practices, security, and compliance
- Build and deploy ML models for forecasting, anomaly detection, and predictive analytics
- Integrate traditional ML with LLM based systems to enable hybrid intelligence workflows
- Develop Python based pipelines for model training, evaluation, and deployment
- Apply prompt engineering, fine tuning strategies, and model orchestration techniques to improve system performance
- Enable AI systems to interact with structured data using optimized SQL queries and semantic models
- Design AI ready data layers (feature stores, curated datasets, vector indexes) on Snowflake
- Collaborate with data teams to ensure high quality, well modeled data pipelines that support AI use cases
- Integrate with Power BI/Fabric to deliver solutions with NL querying and automated insights
- Build intelligent automation using Python, APIs, and orchestration tools
- Develop agent driven workflows for:
- Automated reporting
- Data quality monitoring
- Stakeholder Q&A and decision support
- Integrate AI systems with enterprise tools (Service Now, Salesforce, etc.) for end to end automation
- Work across business, analytics, and engineering teams to identify high impact AI use cases
- Translate technical AI solutions into clear business outcomes and value propositions
- Present architecture decisions, tradeoffs, and governance considerations to stakeholders
- Contribute to best practices, reusable components, and internal AI knowledge sharing
You will have:
- Bachelor's or Master's degree in Computer Science, Data Science, AI, or a related quantitative field
- 4+ years of experience in AI/ML engineering, data engineering, or…
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