Sr. Genai Specialist Psa , Solutions Architecture

Amazon Amazon · Big Tech · Herndon, VA · Solutions Architect

This role is for a Sr. Partner Solutions Architect focused on Generative AI within AWS. The primary responsibility is to work with AWS Partners (ISVs, SIs, consulting firms) to help them build, differentiate, and scale GenAI solutions on AWS. This involves guiding partners on scalable architectures, enabling them to deliver GenAI solutions to their end customers, and converting partner ambition into repeatable, scalable offerings. The role requires deep technical expertise in areas like model selection, fine-tuning, RAG, agentic workflows, and MLOps, as well as the ability to enable partner technical teams and present technical strategies to leadership. The goal is to enable partners to serve hundreds of customers through reusable assets and scalable practices.

What you'd actually do

  1. Build deep technical relationships with AWS Partners (ISVs, SIs, consulting firms) as their trusted GenAI/ML advisor — guiding them in designing cloud-native architectures for LLM-powered applications, agentic systems, and multi-modal AI solutions they can repeatedly deliver to customers.
  2. Co-build with partner engineering teams through end-to-end GenAI development — model selection, RAG implementation, fine-tuning, prompt engineering, and inference optimization — accelerating their time-to-market.
  3. Create reusable reference architectures and delivery accelerators that partners can package into repeatable GenAI offerings across conversational AI, document processing, knowledge assistants, and autonomous agents.
  4. Enable partners to productize LLM-powered agents using Amazon Bedrock Agents, AgentCore, and custom frameworks.
  5. Engage partner leadership and technical teams, drive AWS Competency attainment, and develop lighthouse partners.

Skills

Required

  • 7+ years of design/implementation/operations/consulting with distributed applications experience
  • Experience in written and verbal communication skills to communicate with technical and non-technical audiences, including senior leadership
  • 5+ years customer-facing experience building production AI/ML systems
  • Hands-on GenAI implementation: LLM integration, RAG (vector databases, semantic search), agentic workflows, prompt engineering, model evaluation, and inference optimization
  • Experience with AWS AI/ML services (Amazon Bedrock, SageMaker, AgentCore) or equivalent cloud AI platforms

Nice to have

  • Production GenAI track record — Demonstrated experience shipping GenAI/LLM applications to production at scale, not just POC/prototype stage.
  • Agentic AI depth — building multi-step, tool-using agents with orchestration frameworks (Bedrock Agents, Strands Agents SDK, LangChain, or custom)
  • MLOps/LLMOps — CI/CD p

What the JD emphasized

  • Hands-on GenAI implementation: LLM integration, RAG (vector databases, semantic search), agentic workflows, prompt engineering, model evaluation, and inference optimization
  • Production GenAI track record — Demonstrated experience shipping GenAI/LLM applications to production at scale, not just POC/prototype stage.
  • Agentic AI depth — building multi-step, tool-using agents with orchestration frameworks (Bedrock Agents, Strands Agents SDK, LangChain, or custom)

Other signals

  • enabling partners to build and scale GenAI solutions
  • focus on repeatable, scalable offerings
  • transferring expertise to partners for large-scale deployment