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Senior Full Stack AI Engineer

Senior Full Stack AI Engineer

TadsheenLargo, Florida, United States
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We’re hiring a  Senior Full Stack AI Engineer  who can design and build robust AI-powered systems with a focus on  agentic flows, orchestration logic, and GPU-efficient infrastructure . This role demands strong full-stack engineering skills, a deep understanding of modern AI models, and the ability to build scalable backends that support intelligent agents and dynamic workflows. You’ll own tasks end-to-end and constantly explore new technologies to optimize performance and flexibility.

This position requires strong experience and a proven track record in both software engineering and AI. Candidates must have a demonstrated history of working with well-known organizations in this field and be ready to contribute to a groundbreaking initiative with significance.

Key Responsibilities :

  • Design and implement AI-powered systems with dynamic agentic flows and orchestration logic
  • Build robust APIs that wrap LLMs, embeddings, and vector search for real-world use cases
  • Develop efficient backend infrastructure to support GPU-based inference at scale
  • Own tasks from idea to deployment including prototyping, testing, and performance tuning
  • Explore and apply cutting-edge AI frameworks (LangGraph, CrewAI, etc.)
  • Collaborate across teams while working independently and proactively driving initiatives

We're looking for the best minds to build the future of AI intelligent, scalable, and truly impactful.

  • Strong proficiency in Python and backend programming
  • Hands-on experience with AI systems : LLMs, vector databases, semantic search
  • Familiarity with agentic AI design patterns and orchestration libraries
  • Experience with GPU optimization, model serving (Triton, TorchServe, ONNX), and containerized deployments
  • Ability to independently research, evaluate, and implement new technologies and ideas
  • Experience with LangGraph, CrewAI, AutoGen, or multi-agent coordination
  • Familiarity with MLOps tools like MLflow, Ray, Weights & Biases, or Prefect
  • Understanding of real-time inference strategies, batching, and scaling APIs
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