Experience deploying and maintaining AI/ML models in production environments
Requirements:
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
Job description
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.
