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Role: AI/ML Engineer
Location: Erie, PA (Onsite)
Duration: Long Term
Skills:
8 years of professional experience in AI/ML engineering.
Strong proficiency in Python (advanced level required).
Proven expertise in: LangChain, LangGraph, RAG implementations, Graph RAG.
Knowledge Graph-based AI systems.
Solid foundation in Machine Learning, Deep Learning, and NLP.
Experience deploying AI/ML solutions on cloud platforms such as AWS, Azure, or Google Cloud Platform.
Strong product-building mind-set with the ability to deliver production-grade AI systems.
Comfortable working in environments requiring fast execution, experimentation, and continuous learning.
Client-facing experience and technical leadership are strong pluses.
Responsibilities:
Design and develop scalable Agentic AI solutions, including multi-agent workflows and autonomous AI systems.
Build and optimize RAG pipelines, including advanced implementations such as Graph RAG for enterprise knowledge retrieval.
Develop LLM-powered applications using: LangChain / LangGraph / Vector databases and retrieval frameworks.
Rapidly prototype and deploy AI services using FastAPI and modern Python frameworks.
Work with cutting-edge AI ecosystems including: OpenAI APIs / Hugging Face Transformers / PyTorch.
Collaborate with cross-functional teams to translate business needs into AI-driven technical solutions.
Lead solution development for client-facing AI transformation initiatives.
Mentor junior engineers and contribute to building a strong AI innovation culture.
Stay current with the latest advancements in Agentic AI, LLM orchestration, and retrieval architectures.
Role: AI/ML Engineer
Location: Erie, PA (Onsite)
Duration: Long Term
Skills:
8 years of professional experience in AI/ML engineering.
Strong proficiency in Python (advanced level required).
Proven expertise in: LangChain, LangGraph, RAG implementations, Graph RAG.
Knowledge Graph-based AI systems.
Solid foundation in Machine Learning, Deep Learning, and NLP.
Experience deploying AI/ML solutions on cloud platforms such as AWS, Azure, or Google Cloud Platform.
Strong product-building mind-set with the ability to deliver production-grade AI systems.
Comfortable working in environments requiring fast execution, experimentation, and continuous learning.
Client-facing experience and technical leadership are strong pluses.
Responsibilities:
Design and develop scalable Agentic AI solutions, including multi-agent workflows and autonomous AI systems.
Build and optimize RAG pipelines, including advanced implementations such as Graph RAG for enterprise knowledge retrieval.
Develop LLM-powered applications using: LangChain / LangGraph / Vector databases and retrieval frameworks.
Rapidly prototype and deploy AI services using FastAPI and modern Python frameworks.
Work with cutting-edge AI ecosystems including: OpenAI APIs / Hugging Face Transformers / PyTorch.
Collaborate with cross-functional teams to translate business needs into AI-driven technical solutions.
Lead solution development for client-facing AI transformation initiatives.
Mentor junior engineers and contribute to building a strong AI innovation culture.
Stay current with the latest advancements in Agentic AI, LLM orchestration, and retrieval architectures.