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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Solutions Architect | Python and GenAI - **Company:** Provectus - **Location:** Spain (Remote available) - **Contract:** Permanent contract - **Skills:** Multitier Architecture, Artificial Intelligence, Amazon Web Services, Amazon S3, Cloud Engineering, Code Review, Continuous Integration, Software Design Patterns, Programming Tools, Django Web Framework, Event-Driven Programming, Github, Python (Programming Language), Machine Learning, Node.Js, NoSQL, Object-Oriented Software Development, Performance Tuning, Mockito, SQL Databases, ReactJS, Flask (Web Framework), Large Language Models, Generative AI, Backend, Fastapi, Vue.js, Pytest, Gitlab-ci, Integration Tests, Restful APIs, Streamlit Framework, Amazon Simple Queue Service (SQS), Docker, Microservices - **Published:** August 4, 2026 - **Apply:** https://es.indeed.com/viewjob?jk=b1b0dc2a12786c86 ## About the Role We are looking for a Senior Software Engineer or Solutions Architect with deep Python and Generative AI experience who wants to work this way: deep in the code, close to the client, and directly accountable for whether the system gets used. Direct client communication sits at the center of this role. Prior presales experience is a strong plus., * 7+ years building and running production systems; hands on production experience is required, demo only or POC only backgrounds will not be considered * Production experience with RAG systems and LLM based agentic workflows that are live and running, not prototypes * Backend development experience with Flask, Django REST, or FastAPI * Recent, hands on experience with AWS (SageMaker, Bedrock, Lambda, ECS, S3, SQS, ECR, or similar); GCP considered * Experience with LLM APIs (OpenAI, Anthropic Claude, or AWS Bedrock) * Strong Python proficiency: OOP, design patterns, clean architecture, and performance optimization * Demonstrated experience making and defending system design and architectural trade off decisions * Comfortable owning direct communication with client stakeholders, without a project manager relaying the conversation * Genuine willingness to spend time close to the people who do the job before you design a system to change it, and comfort with an engagement that starts underspecified by design * Strong testing practices: pytest, mocking, and integration tests for AI systems * Experience with Docker and Kubernetes * Understanding of LLM evaluation techniques and quality assurance approaches * Experience deploying and maintaining AI/ML models in production environments * Already using AI assisted development 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 are handed to you * B2+ English, comfortable collaborating across distributed, multicultural teams, * Exposure to Financial Services or Healthcare and Life Sciences, our two primary practice verticals * Presales experience: cost estimation, cloud architecture cost optimization, scoped and phased delivery plans * Prior consulting, professional services, or other embedded client facing delivery * Experience with React or Vue * AWS or Claude Code certifications * 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) ## Description * Embed with the client team for the length of the engagement, working inside their environment rather than alongside it from a distance * Spend time with the people who do the job the system is meant to change before you design anything, so the architecture is grounded in how the work actually happens * Write clean, production grade Python across AI integrations, backend services, and RESTful APIs (Flask, Django, or FastAPI) * Design, build, and optimize RAG systems and agentic AI solutions running in production, not demos or notebooks * Own system design and architectural decisions across the engagement: microservices vs monolith, sync vs event driven, SQL vs NoSQL * Own the technical direction of the engagement from discovery through delivery * Act as the client's direct technical point of contact: present architecture, defend trade offs, and push back on scope when it does not match timeline or budget * Support presales activities where relevant, including discovery calls, technical proposals, scoping, and client facing demos * Lead architecture reviews, produce technical design documents, and contribute to standards across the Python practice * Feed what you learn back into Provectus's blueprint library, so the next engagement starts further ahead * Mentor engineers, lead code reviews, and share knowledge across the team, * Full ownership of production engagements, not a review and hand off role * Access to Provectus's blueprint library, built from every engagement we have shipped * 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 first within Europe, 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 ## Related Videos - [Leveraging Real time data in FSIs](https://www.wearedevelopers.com/videos/806-leveraging-real-time-data-in-fsis) - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [Innovating Developer Tools with AI: Insights from GitHub Next](https://www.wearedevelopers.com/videos/1268-innovating-developer-tools-with-ai-insights-from-github-next) - [Should we build Generative AI into our existing software?](https://www.wearedevelopers.com/videos/1129-should-we-build-generative-ai-into-our-existing-software) - [Tomorrow's cloud data platforms - fully managed database-as-a-service (DBaaS)](https://www.wearedevelopers.com/videos/254-tomorrow-s-cloud-data-platforms-fully-managed-database-as-a-service-dbaas) - [Make it simple, using generative AI to accelerate learning](https://www.wearedevelopers.com/videos/969-make-it-simple-using-generative-ai-to-accelerate-learning) ## Related Articles - [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering) - [What is Agentic Programming and Why Should Developers Care?](https://www.wearedevelopers.com/magazine/625-what-is-agentic-programming-and-why-should-developers-care) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Dev Digest 121 - AI goes offline](https://www.wearedevelopers.com/magazine/456-dev-digest-121-ai-goes-offline) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [From Prototype to Production: Build AI Agents with This Free 4-Course Learning Path](https://www.wearedevelopers.com/magazine/655-from-prototype-to-production-build-ai-agents-with-this-free-4-course-learning-path)