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Salary
$131k – $283k per year (Estimated)
Location
Remote/Hybrid (Newark, United States)
Employment
Full-Time
Overview
Company
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About BayRock Labs

At BayRock Labs, we pioneer innovative tech solutions that drive business transformation. As a leading product engineering firm based in Silicon Valley, we provide full-cycle product development, leveraging cutting-edge technologies in AI, ML, and data analytics. Our collaborative, inclusive culture fosters professional growth and work-life balance. Join us to work on ground-breaking projects and be part of a team that values excellence, integrity, and innovation. Together, let's redefine what's possible in technology.

We are seeking a highly skilled AI Engineer with strong hands-on experience in building and integrating LLM-powered systems. The ideal candidate will have deep expertise in Python, practical experience with LangGraph/LangChain for agent workflows, and proficiency in FastAPI for developing production-grade APIs. This role involves designing, deploying, and scaling intelligent systems that leverage large language models to deliver enterprise-ready solutions.

Key Responsibilities

  • Design and build advanced AI systems powered by large language models (LLMs).
  • Develop and integrate agent workflows using LangGraph/LangChain frameworks.
  • Implement production-grade APIs with FastAPI to support scalable deployments.
  • Collaborate with cross-functional teams (data scientists, ML engineers, product managers) to deliver end-to-end AI solutions.
  • Optimize performance, reliability, and scalability of AI-driven applications.
  • Stay current with emerging AI/ML technologies and contribute to innovation initiatives.

Required Skills & Experience

  • Strong hands-on experience with LLM-powered systems (e.g., GPT, Claude, LLaMA, Mistral).
  • Deep expertise in Python for AI/ML development.
  • Proven experience with LangGraph/LangChain for agent workflow orchestration.
  • Proficiency in FastAPI for building robust, production-ready APIs.
  • Solid understanding of ML lifecycle management, including deployment, monitoring, and scaling.
  • Experience with cloud platforms (Azure, AWS, or GCP) for AI/ML workloads.
  • Strong problem-solving skills and ability to work in fast-paced environments.

Preferred Qualifications

  • Experience with vector databases (e.g., Pinecone, Weaviate, FAISS) for retrieval-augmented generation.
  • Familiarity with MLOps tools (MLflow, Kubeflow, or similar).
  • Knowledge of prompt engineering and fine-tuning LLMs.
  • Prior work in enterprise AI applications (chatbots, copilots, automation systems).
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