Python Solutions Architect (GenAI)

    ~$57,512 - $106,808Market Estimate
    Serbia && Spain && Poland && Yerevan && Tbilisi
    Full-Time
    Mid (3-6 yrs)
    Engineering & Development
    Posted on September 15, 2026
    About The Role:
    Provectus is a global AI and cloud consulting company helping enterprises turn artificial intelligence and data into production-ready business solutions. We specialize in designing, building, and scaling end-to-end AI/ML systems, data platforms, and cloud-native architectures, with strong expertise in AWS, MLOps, and enterprise-grade AI delivery.
    We are an official Anthropic partner, working with cutting-edge foundation models to help organizations safely and effectively adopt advanced AI capabilities.
    Our consulting teams operate across industries such as finance, healthcare, retail, and technology, delivering solutions with measurable business impact through hands-on engineering and advisory.
    As a Solutions Architect, you will drive the development of GenAI-powered solutions, including AI agents, RAG systems, and Python services. You will provide technical leadership, own solution architecture, mentor engineers, and guide projects from discovery to production.
    What You’ll Bring:
    Mindset
  1. Full-stack mindset, comfortable across AI, backend development, and cloud infrastructure
  2. Already using AI tools in your daily workflow (Claude Code, Copilot, or similar)
  3. Proactive and self-directed; you own outcomes end-to-end and spot problems before they're handed to you
  4. B2+ English, comfortable collaborating across distributed, multicultural teams
  5. Presales & Client Engagement
  6. 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
  7. Produces scoped, phased delivery plans with clear deliverables, dependencies, and risks
  8. Experience with cost estimation and cloud architecture cost optimization
  9. Python, AI & Cloud
  10. 7+ years building and running production systems not only demos and POCs
  11. Strong understanding of AI/ML concepts and experience integrating AI/ML components into solutions
  12. Strong Python proficiency: OOP, design patterns, clean architecture, and performance optimization
  13. Experience building RESTful APIs with FastAPI, Django REST, or Flask
  14. Experience making and defending architectural trade-off decisions: microservices vs monolith, sync vs event-driven, SQL vs NoSQL
  15. Strong testing practices: pytest, mocking, and integration tests for AI systems
  16. Experience with Docker and Kubernetes
  17. Hands-on experience building production LLM-based applications and agentic workflows
  18. Experience with LLM APIs (OpenAI, Anthropic, or AWS Bedrock)
  19. Experience building and optimizing RAG systems
  20. Understanding of LLM evaluation techniques and quality assurance approaches
  21. Experience deploying and maintaining AI/ML models in production environments
  22. Hands-on experience with AWS (SageMaker, Bedrock, Lambda, ECS, S3, SQS, ECR, or similar); GCP considered
  23. Experience with React/Vue
  24. AWS and Claude Code Certifications
  25. Nice to Have

  26. Experience with Streamlit or Gradio for AI prototyping
  27. Modern Python tooling (ruff, uv, pyproject.toml, pyright)
  28. CI/CD pipeline experience (GitHub Actions, GitLab CI)
  29. Experience in an additional language (Go, Node.js, or Rust)
  30. Front-end experience
  31. What You’ll Do:
  32. Write clean, production-grade Python across AI integrations, backend services, and RESTful APIs
  33. Implement and optimize RAG systems for production use cases
  34. Design and build LLM-based and agentic AI solutions that address real client business challenges
  35. Own the technical direction of client engagements from discovery through delivery
  36. Support presales: discovery calls, technical proposals, scoping, and client-facing demos
  37. Lead architecture reviews, produce technical design documents, and contribute to standards across the Python practice
  38. Mentor engineers, lead code reviews, and share knowledge across the team
  39. Build and maintain strong relationships with key client stakeholders as a trusted technical advisor
  40. What We Offer:
  41. Opportunity to work with cutting-edge AI and cloud solutions
  42. Internal training programs (Leadership, Public Speaking, and more) with full support for AWS and other professional certifications
  43. Career growth: a clear path toward SA or beyond; we actively develop our engineers
  44. Access to the latest AI tools and premium subscriptions
  45. Long-term B2B collaboration
  46. Remote with flexible hours
  47. Private medical insurance or a budget for your medical needs
  48. Paid sick leave, vacation, and public holidays
  49. Equipment and all the tech you need for comfortable, productive work
  50. Company:  Provectus

    AI systems integrator building and operating production AI and data systems for enterprises.
    201-500 employees
    AI & Machine Learning
    HQ: United States