Sr. Full Stack AI Engineer 181801

Example Use Cases

Representative initiatives may include developing AI-powered capabilities that improve advisor effectiveness and client engagement, such as:

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  Automated meeting preparation and research
  
  

  
  


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  Intelligent call summarization and insight generation
  
  

  
  


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  Automated follow-up and workflow orchestration
  
  

  
  


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  Knowledge retrieval and recommendation systems
  
  

  
  


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  AI-assisted decision support and productivity tools
  
  

  
  


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  Workflow automation leveraging enterprise data sources and communication channels
  
  

  
  

The Skills You Bring

• Bachelor's degree or equivalent experience with 5+ years of software engineering experience.
  
  


• Proven experience designing and delivering scalable, production-grade software solutions and distributed systems.
  
  


• Strong experience using LLMs and Generative AI technologies to solve real business challenges
  
  


• Strong full-stack engineering background with modern languages and frameworks such as Python, TypeScript, Node.js, APIs, React, and Next.js.
  
  


• Hands-on experience deploying and scaling applications within cloud environments such as AWS, Azure, or Google Cloud.
  
  


• Experience with modern platform engineering and DevOps practices, including containers, Kubernetes, Infrastructure-as-Code, and cloud-native architectures.
  
  


• Strong understanding of software architecture, design patterns, security, and reliability principles for enterprise-scale applications.
  
  


• Excellent problem-solving skills, sound technical judgment, and a passion for building innovative solutions.
  
  


• Ability to collaborate effectively across engineering, data, product, and business teams while driving initiatives from concept to production.
  
  

Ultimately, I need a hands-on Senior AI Engineer who combines GenAI/LLM experience, strong software and data engineering fundamentals, and cloud platform expertise to design, build, and deploy AI solutions that solve real business challenges, enhance advisor efficiency, and automate key processes at scale.