Principal AI Engineer

New

Remote (Global)Full-TimePrincipal

Salary not disclosed

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Job Details

Deep expertise in Python with an emphasis on maintainable architecture, object-oriented design, and async execution.
Strong grasp of software architecture principles and system-level design.
Experience with Docker and modern CI/CD practices.
Hands-on work with agent-oriented frameworks including LangChain, LangGraph, or LlamaIndex.
Practical experience optimizing LLM behavior through prompt strategies, context orchestration, and lightweight fine-tuning approaches.
Solid understanding of core ML concepts such as embeddings, evaluation techniques, and performance trade-offs.
Experience implementing vector-based retrieval using platforms like Pinecone or Qdrant.
Working familiarity with graph databases (e.g., Neo4j) for modeling relationships and knowledge.
Strong SQL skills and experience with relational data modeling.
Proven experience deploying ML solutions using services such as SageMaker, Vertex AI, or Azure Machine Learning.

Lead the creation of scalable AI platforms, including retrieval-augmented generation solutions and multi-step agent-based processes using modern orchestration frameworks.
Develop robust, testable, and secure services ready for real-world use, supporting deployment workflows and contributing to operational best practices.
Act as a hands-on technical advisor during client engagements, transforming loosely defined business needs into concrete system designs and implementation plans.
Architect and implement data backends that combine structured databases, vector search engines, and graph-based knowledge systems for advanced AI reasoning.
Deploy and operate AI workloads on leading cloud ecosystems such as AWS, Azure, or GCP, focusing on security, scalability, and cost efficiency.

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