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.