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Python/genai solutions architect

USA · Job Posted May 27, 2026
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Job Responsibility

  • Write clean, production-grade Python across AI integrations, backend services, and RESTful APIs
  • Implement and optimize RAG systems for production use cases
  • Design and build LLM-based and agentic AI solutions that address real client business challenges
  • Own the technical direction of client engagements from discovery through delivery
  • Support presales: discovery calls, technical proposals, scoping, and client-facing demos
  • Lead architecture reviews, produce technical design documents, and contribute to standards across the Python practice
  • Mentor engineers, lead code reviews, and share knowledge across the team
  • Build and maintain strong relationships with key client stakeholders as a trusted technical advisor

Requirements

  • Full-stack mindset, comfortable across AI, backend development, and cloud infrastructure
  • Already using AI tools in your daily workflow (Claude Code, Copilot, or similar)
  • Proactive and self-directed
  • you own outcomes end-to-end and spot problems before they're handed to you
  • B2+ English, comfortable collaborating across distributed, multicultural teams
  • Owns the client technical relationship
  • leading discovery, decomposing ambiguous requirements into technical components, presenting architecture, and pushing back on scope when it doesn't match timeline or budget
  • Produces scoped, phased delivery plans with clear deliverables, dependencies, and risks
  • Experience with cost estimation and cloud architecture cost optimization
  • 7+ years building and running production systems, not only demos and POCs
  • Strong understanding of AI/ML concepts and experience integrating AI/ML components into solutions
  • Strong Python proficiency: OOP, design patterns, clean architecture, and performance optimization
  • Experience building RESTful APIs with FastAPI, Django REST, or Flask
  • Experience making and defending architectural trade-off decisions: microservices vs monolith, sync vs event-driven, SQL vs NoSQL
  • Strong testing practices: pytest, mocking, and integration tests for AI systems
  • Experience with Docker and Kubernetes
  • Hands-on experience building production LLM-based applications and agentic workflows
  • Experience with LLM APIs (OpenAI, Anthropic, or AWS Bedrock)
  • Experience building and optimizing RAG systems
  • Understanding of LLM evaluation techniques and quality assurance approaches
  • Experience deploying and maintaining AI/ML models in production environments
  • Hands-on experience with AWS (SageMaker, Bedrock, Lambda, ECS, S3, SQS, ECR, or similar)
  • GCP considered
  • Experience with React/Vue
  • AWS and Claude Code Certifications

Nice to have

  • Experience with Streamlit or Gradio for AI prototyping
  • Modern Python tooling (ruff, uv, pyproject.toml, pyright)
  • CI/CD pipeline experience (GitHub Actions, GitLab CI)
  • Experience in an additional language (Go, Node.js, or Rust)
  • Front-end experience

What we offer

  • Opportunity to work with cutting-edge AI and cloud solutions
  • Internal training programs (Leadership, Public Speaking, and more) with full support for AWS and other professional certifications
  • Career growth: a clear path toward SA or beyond
  • Access to the latest AI tools and premium subscriptions
  • Remote with flexible hours
  • Unlimited Vacation policy
  • Generous health, vision, and dental insurance
  • 401(K) matching plan

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