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Design and implement cloud-native AI solutions, focusing on RAG systems and agentic workflows to solve client business challenges. Act as a technical advisor throughout the project lifecycle, from presales discovery and scoping to production delivery and mentoring.
Design and build cloud-native data, LLM-based, and agentic AI solutions addressing real client business challenges
Implement and optimize RAG systems for production use cases
Build and maintain strong relationships with key customer stakeholders, acting as a trusted technical advisor.
Support presales: discovery calls, technical proposals, scoping, and client-facing demos
Own the technical direction of client engagements from discovery through delivery — the go-to authority for clients and the internal team
Write clean, production-grade Python across AI integrations, backend services, and RESTful APIs
Build and maintain ETL/ELT workflows using modern orchestration and distributed computing tools.
Deploy ML and LLM-based solutions
Implement MLOps, LLMOps, and AgentOps practices: CI/CD, automated testing, model monitoring, and experiment tracking.
Lead architecture reviews, produce technical design documents, and contribute to standards
Mentor engineers, lead code reviews, and share knowledge across the team.
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