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Architect ML​/GenAI IRC

Job in Town of Poland, Jamestown, Chautauqua County, New York, 14701, USA
Listing for: GlobalLogic
Full Time position
Listed on 2026-06-10
Job specializations:
  • Software Development
    AI Engineer (Applied/Software), Machine Learning/ ML Engineer, Data Scientist
Salary/Wage Range or Industry Benchmark: 140000 - 180000 USD Yearly USD 140000.00 180000.00 YEAR
Job Description & How to Apply Below
Position: Architect ML/GenAI IRC296973
Location: Town of Poland

We are seeking a highly skilled GenAI Engineer to design, build, and deploy Large Language Model (LLM)–driven applications and intelligent agent systems. The role blends prompt engineering, pipeline design, and software development with MLOps and data engineering to deliver scalable, production-grade GenAI solutions.

Requirements
  • Master’s / Ph.D. in Computer Science, Data Science, Applied Mathematics, or a related field.
  • 7+ years of experience in software or ML engineering
  • 4+ years in LLM / GenAI development.
  • Strong Python programming skills and experience with ML/AI stacks
  • Hands‑on experience with LLM APIs (OpenAI, Anthropic, Mistral, Hugging Face)
  • Experience building RAG pipelines (FAISS, Weaviate, Chroma, Milvus) and with vector embeddings.
  • Familiarity with agent frameworks (Lang Chain, DSPy, CrewAI, Lang Graph).
  • Knowledge of cloud AI platforms (Vertex AI, Sage Maker, Bedrock, Azure OpenAI) and MLOps principles.
  • Practical understanding of data engineering (ETL, data cleaning, schema structuring).
  • Excellent problem‑solving skills.
  • Excellent analytical, communication, and teamwork skills.
Preferred
  • Experience in fine‑tuning or adapting LLMs.
  • Exposure to multimodal GenAI and contextual evaluation tools.
  • Familiarity with GenAI UX development (Streamlit, Gradio, React-based chat UIs).
Job responsibilities
  • Design, implement, and optimize GenAI pipelines.
  • Develop prompt engineering frameworks.
  • Build agentic systems using various frameworks for autonomous and/or multi-step reasoning.
  • Architect and deploy GenAI APIs and services.
  • Establish LLMOps practice: versioning, benchmarking, and monitoring.
  • Collaborate with data engineers on ETL and knowledge ingestion pipelines.
  • Implement GenAI UX layers (chat interfaces, dashboards, plugins).
  • Support pre‑sales PoCs and cross‑functional demos showcasing GenAI capabilities.
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