Tech Lead / Solutions Architect

Role Description

• 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

Qualifications

• 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

Requirements

• 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
• 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

Benefits

• Opportunity to work with cutting-edge AI and cloud solutions
• 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