Python/GenAI Tech Lead

What You’ll Do:

• 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.

What You’ll Bring:

Mindset
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.

What We Offer:

• Opportunity to work with cutting-edge AI and cloud solutions.
• Career growth: a clear path toward SA or beyond  — we actively develop our engineers.
• Access to the latest AI tools and premium subscriptions.
• Remote with flexible hours.
• Long-term B2B collaboration;
• A budget for your medical insurance;
• Paid sick leave, vacation, public holidays;
• Continuous learning support, including unlimited AWS certification sponsorship.