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Design and implement agentic AI systems with structured interfaces, reasoning loops, and robust error handling
Build and maintain data pipelines, scheduled workflows, and benchmarking infrastructure
Develop evaluation and scoring systems to measure and continuously improve model output quality
Integrate the platform with internal and external services, including ticketing, messaging, storage, and observability
Collaborate with cross-functional teams to translate business requirements into technical AI solutions
Architect and maintain production-grade AI solutions with focus on scalability, reliability, and performance
SW development, Strong Python with applications in AL/ML
Familiarity with AI agents and their applications, including prompt design, tool calling, context management, and evaluation
Experience or strong interest in Data Science and Engineering
Experience or strong interest in creating Analytical or AI/ML-based models for real-world problems
Strong problem-solving skills, especially in simplifying and modelling real-world problems
Familiarity with major LLM providers (OpenAI, Anthropic, Google, Meta, etc.) and understanding of their trade-offs in terms of performance, cost, latency, and capabilities
Experience integrating AI capabilities into applications or eagerness to learn application development
Full-stack development experience with both backend and frontend technologies
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