Senior Python & GenAI Solutions Architect - Remote

Jobgether; United States; On-site; USD 140,000 - 190,000; Full time

Benefits offered by this job

Remote-friendly working environment

Performance-based bonuses

401(k) matching

Job summary

Jobgether is seeking a senior Python/GenAI Solutions Architect based in the United States. The role combines deep Python expertise with hands-on generative AI delivery, translating real operational needs into production AI systems within client environments.

You will design and build RAG systems, agentic AI workflows, and cloud-native architectures for enterprise-scale deployments, with direct client engagement and presales involvement as part of the responsibilities.

Qualifications

• 7+ years of experience building and operating production software systems, with substantial hands‑on engineering experience.
• Demonstrated production experience designing and operating RAG systems and LLM‑based agentic workflows.
• Strong Python development expertise, including object‑oriented programming, design patterns, clean architecture, performance optimization, and maintainable software design.
• Professional experience with backend frameworks such as Flask, Django REST, or FastAPI.
• Recent hands‑on experience with AWS services such as SageMaker, Bedrock, Lambda, ECS, S3, SQS, ECR, or comparable cloud technologies. GCP experience is also considered.
• Experience integrating LLM APIs such as OpenAI, Anthropic Claude, or AWS Bedrock.
• Demonstrated ability to make, communicate, and defend system architecture and technical trade‑off decisions.
• Comfortable communicating directly with client stakeholders and independently leading technical conversations without relying on a project manager to act as an intermediary.
• Genuine interest in understanding users and operational workflows before designing technology solutions, including the ability to work effectively when engagements begin with incomplete or evolving requirements.
• Strong software testing practices, including pytest, mocking, integration testing, and testing approaches specific to AI systems.
• Experience with Docker and Kubernetes.
• Understanding of LLM evaluation techniques, AI quality assurance, and methods for assessing the reliability and effectiveness of AI‑powered systems.
• Experience deploying, operating, and maintaining AI/ML models in production environments.
• Regular use of AI‑assisted development tools such as Claude Code, GitHub Copilot, or comparable tools.
• Proactive, self‑directed approach with strong ownership of technical outcomes from discovery through production.
• Strong problem‑solving skills and the ability to identify and address issues before they become delivery blockers.
• B2+ English proficiency and the ability to collaborate effectively with distributed, multicultural teams.
• Exposure to Financial Services or Healthcare and Life Sciences is a plus.
• Presales experience involving cost estimation, cloud architecture optimization, delivery scoping, or phased implementation planning is preferred.
• Previous consulting, professional services, or embedded client‑facing delivery experience is advantageous.
• Experience with React or Vue is a plus.
• AWS or Claude Code certifications are beneficial.
• Experience with Streamlit or Gradio for AI prototyping is a plus.
• Familiarity with modern Python tooling such as ruff, uv, pyproject.toml, and pyright is desirable.
• Experience with CI/CD platforms such as GitHub Actions or GitLab CI is beneficial.
• Experience with an additional programming language such as Go, Node.js, or Rust is a plus.

Responsibilities

• Embed directly with client teams, working within their environments and collaborating closely with stakeholders to improve workflows.
• Conduct discovery with end users and stakeholders to understand processes, pain points, and requirements before defining technical solutions.
• Develop production-grade Python across AI integrations, backend services, and RESTful APIs using frameworks like Flask, Django REST, or FastAPI.
• Design, build, deploy, and optimize production RAG systems and agentic AI solutions for enterprise scale.
• Own system architecture and technical decisions across engagements, evaluating microservices vs monoliths and SQL vs NoSQL choices.
• Lead the technical direction from discovery through implementation, deployment, optimization, and production support.
• Serve as primary technical contact for clients, presenting architecture, trade‑offs, and managing expectations.
• Support presales activities including discovery sessions, proposals, scoping, cost estimation, and client demos.
• Lead architecture reviews and create technical design documentation, standards, and reusable patterns.
• Contribute to internal blueprint libraries and delivery frameworks to improve future engagements.
• Mentor engineers, lead code reviews, and promote engineering best practices across Python and AI teams.
• Evaluate AI system quality and reliability through testing, monitoring, and QA practices.

Skills

Python

GenAI / LLM

RAG systems

Architecture leadership

Cloud (AWS/GCP)

Docker & Kubernetes

REST APIs

Client engagement

Pre-sales / cost estimation

Testing (pytest)

Tools

Docker

Kubernetes

AWS

GCP

OpenAI API

Claude

Bedrock

SageMaker

Job description

Jobgether is seeking a senior Python/GenAI Solutions Architect based in the United States. The role combines deep Python expertise with hands-on generative AI delivery, translating real operational needs into production AI systems within client environments.

You will design and build RAG systems, agentic AI workflows, and cloud-native architectures for enterprise-scale deployments, with direct client engagement and presales involvement as part of the responsibilities.