Python Solutions Architect (GenAI)

Provectus
Inconnu, France
18 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
7 years minimum
Working hours
Regular working hours
Languages
English
Job source

Tech stack

Multitier Architecture Artificial Intelligence Amazon Web Services Amazon S3 Cloud Computing Cloud Engineering Code Review Continuous Integration Software Design Patterns Django Web Framework Github Python (Programming Language)
+27 more
Machine Learning Node.Js NoSQL Object-Oriented Software Development Performance Tuning Software Tools Mockito SQL Databases Systems Integration ReactJS Flask (Web Framework) Large Language Models Backend Fastapi Vue.js Build Management Pytest Gitlab-ci Integration Tests Data Management Machine Learning Operations Front End Software Development Restful APIs Streamlit Framework Amazon Simple Queue Service (SQS) Docker Microservices

Job description

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., * 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, * 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; we actively develop our engineers
  • Access to the latest AI tools and premium subscriptions
  • Long-term B2B collaboration
  • Remote with flexible hours
  • Private medical insurance or a budget for your medical needs
  • Paid sick leave, vacation, and public holidays
  • Equipment and all the tech you need for comfortable, productive work

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

Presales & Client Engagement

  • 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

Python, AI & Cloud

  • 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

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