À propos de ce poste Python/GenAI Solutions Architect chez Provectus
About the Role:
Provectus is a consulting and professional services firm with a focus on AI/ML based solutions. Provectus is an AWS Premier Partner and an Anthropic partner, helping enterprise clients move from AI experimentation to AI running in production.
We are changing how we deliver. Instead of handing a client a design and waiting for someone else to build it, our engineers embed directly inside the client's team and ship the system themselves. We call this Forward Deployed delivery. Before you design anything, you spend real time with the people who do the work the system is meant to change, so the architecture reflects how the work actually happens, not how a requirements document described it.
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.
What You’ll Do:
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
What You’ll Bring:
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
Nice to Have:
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)
