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:
- 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.
- 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.
- 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.
Mindset
Presales & Client Engagement
Python, AI & Cloud
Nice to Have
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.
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