Sr. AI Solution Architect

Amazon Amazon · Big Tech · AR, Buenos Aires · Solutions Architect

This role is for a Sr. AI Solution Architect at AWS who will work with customers to design and implement production-ready generative AI and agentic AI solutions on the cloud. The role involves building technical relationships, advising on AI/ML adoption, and influencing the product roadmap.

What you'd actually do

  1. Build trusted technical relationships with customers of all sizes, serving as their advisor for GenAI/ML and Agentic AI adoption across their cloud journey
  2. Manage technical relationships between AWS and customers, providing recommendations on security, cost, performance, reliability, and operational efficiency to accelerate AI/ML projects
  3. Act as voice of customer internally, sharing feedback and requirements to influence the AWS GenAI/ML and Agentic features roadmap
  4. Design cloud-native architectures that link technology to tangible solutions, defining GenAI/ML and Agentic architectural patterns for diverse use cases
  5. Create and share technical content including whitepapers, code samples, blog posts, and reference architectures; evangelize AWS AI capabilities through workshops, conferences, meetups, and online channels

Skills

Required

  • 4+ years of experience in designing and implementing application and infrastructure solutions
  • 3+ years of technical customer engagement and resource management experience
  • 3+ years of production AI system design experience
  • Hands-on experience with cloud platforms and AI/ML services to build secure AI environments and implement RAG using embeddings, vector stores, and semantic search.
  • Strong communication skills with ability to influence technical and business decision-makers across diverse audiences

Nice to have

  • Cloud technology certification (AWS, Azure, or GCP Solutions Architect or equivalent)
  • Advanced degree in computer science, mathematics, statistics, machine learning, or related quantitative field
  • Experience with LLM optimization techniques (e.g., LoRA/QLoRA, Instruction Tuning, RLHF) for domain-specific tasks
  • Expertise in architecting AI systems for highly regulated or security-sensitive environments (Financial Services, Healthcare, Public Sector)
  • Proven track record of leading complex, innovative technology initiatives with measurable business impact
  • Hands-on experience with cloud AI/ML services (e.g., AWS Bedrock/SageMaker, Azure OpenAI Service/Azure ML, Google Vertex AI) for production RAG implementations

What the JD emphasized

  • production AI system design experience
  • Hands-on experience with cloud platforms and AI/ML services to build secure AI environments and implement RAG using embeddings, vector stores, and semantic search.
  • Experience with LLM optimization techniques (e.g., LoRA/QLoRA, Instruction Tuning, RLHF) for domain-specific tasks
  • Expertise in architecting AI systems for highly regulated or security-sensitive environments (Financial Services, Healthcare, Public Sector)

Other signals

  • customer-facing
  • architecting AI solutions
  • generative AI
  • agentic AI