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Strong Tier-1 brand, metro hybrid role, in-demand LLM/agent skillset, and broad mid-level requirements increase competition.
Specialized LLM and agent engineering skills transfer across industries but require AI-specific experience, so medium sensitivity.
Explicit 1–3 years requirement plus mandatory LLM inference, Python, and agent/integration skills makes screening strict.
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Develop and evolve Flutter's enterprise AI assistant and multi-agent platforms, integrating with internal applications and data sources across the organisation.
Lead design and implementation of LLM inference systems (LiteLLM, AWS Bedrock) focusing on scalable, efficient AI applications with context engineering and prompt architecture.
Build secure, compliant AI systems including guardrails and agentic AI architectures (LangChain, LangGraph, Strands, ADK), delivering full-stack AI solutions with cross-functional collaboration.
Bachelor's degree in computer science, AI, or related STEM field.
1–3 years of hands-on AI/ML or software development experience.
Proficiency in Python with experience in frameworks like FastAPI or Flask and async programming.
Experience with LLM inference platforms (AWS Bedrock and/or LiteLLM), context engineering, model tokenomics, agent frameworks, and AI security practices.
Experienced in agentic AI frameworks and multi-agent orchestration with understanding of token economics and retrieval-augmented generation.
Skilled at designing secure, compliant AI systems suitable for regulated environments like gaming or finance.
Capable of full-stack AI application ownership with strong cross-team communication and usage of AI-augmented development tools (Claude Code, GitHub Copilot).