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Mid-level metro role at a known global employer with sought-after LLM skills increases applicant competition.
Requires specialized LLM, agent frameworks and production ML experience, limiting cross-industry transferability.
Explicit 5–10 years requirement plus mandatory LLM, MLOps, cloud, and tooling skills makes filtering strict.
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Design and build AI-powered automation solutions for complex, repetitive, or decision-driven tasks across multiple service functions.
Develop, optimize, and industrialize AI and agentic solutions including LLM integrations, APIs, event-driven pipelines, and AI governance for production-grade deployment.
Partner with business stakeholders to identify automation opportunities, deliver AI value, and ensure responsible AI practices and compliance.
Bachelor’s or Master’s degree in Computer Science, AI, Machine Learning, Data Science, or related field; PhD advantageous for AI Exploration track.
5-10 years of experience in software engineering, AI engineering, or related technical disciplines with demonstrated AI solution delivery or prototyping.
Proficient in Python (including testing and asynchronous programming), SQL required; Java or C#/.NET is a plus.
Hands-on experience with LLM and agent frameworks (LangChain, LangGraph, Semantic Kernel, etc.), cloud AI platforms (Azure AI Foundry, Azure OpenAI), and AI model optimization and evaluation techniques.
Experienced in delivering or prototyping advanced AI solutions at scale within enterprise or shared services environments, bridging business and technical needs.
Strong expertise in LLMs, multimodal AI, AI governance, and end-to-end AI engineering from model development through deployment and observability.
Comfortable working cross-functionally with global teams in Agile environments, with practical knowledge of AI evaluation, security, and compliance requirements.