3 kernel jobs at 3 companies in Concord, NC

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Principal Engineer - Agentic AI Engineering
Charlotte, North Carolina, United States
OnsiteFull Time
Bank of America
Bank of AmericaNYSE: BAC: Provides global banking, investing, and financial risk management services.
7+ YOE7+ years software engineering experience; hands-on with GitHub Copilot, LangGraph, Semantic Kernel/Microsoft Agent Framework, SDLC automation, CI/CD, secure coding; experience in regulated environments; bachelor’s degree in a technical field.
GitHub Copilot, LangGraph, Semantic Kernel, Microsoft Agent Framework, SDLC, CI/CD
2mo
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Artificial Intelligence/Machine Learning Data Engineer
Charlotte or Morristown or Jersey City or Cleveland or California or Colorado or District of Columbia or Illinois or Maryland or Massachusetts or Minnesota or New York or New Jersey or Washington
$44-$54/hr HybridFull Time
Accenture
AccentureNYSE: ACN: Global provider of management consulting and technology services.
5+ YOEMinimum 5 years in data/ML/AI or software engineering; strong Python and SQL; experience with LLMs, agent frameworks (LangChain, Semantic Kernel, LlamaIndex, AutoGen), ML deployment and data pipelines; Associate's degree required.
MLflow, Azure ML, SageMaker, Kubeflow, TensorFlow, PyTorch, Scikit-Learn, Spark, Databricks, FAISS, Pinecone, Chroma, Milvus, Redis, CI/CD, Docker, Kubernetes, Azure, AWS, GCP, Kafka, EventHub, Kinesis, LangChain, Semantic Kernel, LlamaIndex, AutoGen, Python, SQL, Scala, Java, Go
3mo
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Agentic AI Engineer
Charlotte, North Carolina, United States
OnsiteFull Time
Hoffman & Hoffman
Hoffman & Hoffman: Provides commercial HVAC, building automation, and mechanical service solutions.
1+ YOEStrong Python backend experience; 1+ year with LLM agents; experience with agentic stacks (LangChain, Semantic Kernel, AutoGen, CrewAI, LangGraph) and cloud AI (Azure OpenAI, GCP, AWS); knowledge of prompts, RAG, and MLOps.
Python, LangChain, Semantic Kernel, AutoGen, CrewAI, LangGraph, Azure OpenAI, Google Cloud, AWS, REST, GraphQL, Databases, Messaging, Microservices, MLOps