The role involves designing and implementing Python services and AI solutions, leading technical engagements, and mentoring engineers. Responsibilities include production-level coding, architecture decisions, and client interaction.
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
- 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
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