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Strong employer brand, metro location, hybrid, and mid-level generalist AI role increase competition.
Core LLM, agent, and Python skills transferable across industries, though regulated-experience preference raises specificity.
Explicit 1–3 years plus specialized LLM, agent, and security skills make filters stringent.
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Develop and evolve Flutter's enterprise AI assistant and multi-agent platforms to enhance productivity and decision-making across global sports betting and gaming operations.
Design and implement LLM inference systems using LiteLLM and AWS Bedrock, focusing on scalable, cost-efficient AI applications with advanced context engineering and prompt architecture.
Build agentic AI solutions using frameworks like LangChain and ADK; own end-to-end AI application delivery including integrations with AWS services and ensuring security-compliant AI outputs.
Bachelor's degree in computer science, AI, or related STEM field.
1–3 years of hands-on AI/ML or software development experience.
Practical experience with Python (including FastAPI or Flask) and LLM inference platforms, particularly AWS Bedrock and/or LiteLLM.
Familiarity with agentic AI frameworks (LangChain, LangGraph, Strands, or ADK) and security risks related to AI systems.
Experienced in AI platform development with a focus on integrating AI solutions within enterprise environments under regulatory constraints.
Skilled in balancing AI model tokenomics including latency, cost, and performance trade-offs in production systems.
Demonstrates capability to work across full-stack AI application development, collaborating cross-functionally and applying security-first practices.