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Specialized LLM/agentic engineering profile reduces generic applicants, yielding moderate competition.
LLM engineering skills transfer broadly, but production AI privacy and domain constraints increase sensitivity.
Senior production LLM, TypeScript/Node and cloud-native experience are required, creating strict filtering.
Design, build, and operate AI-powered features using large language models (LLMs) and agentic systems to deliver measurable impact at scale.
Own AI feature lifecycle: identify opportunities, shape architecture, prototype, integrate, monitor, and improve production systems.
Provide technical leadership including defining reusable AI engineering patterns, guiding engineers, and making decisions on performance, security, privacy, and cost.
Strong software engineering experience with scalable, production-grade system design and operation.
Proficient in TypeScript and Node.js backend development, including APIs and service integrations.
Practical experience using large language models (e.g., OpenAI, Anthropic, Amazon Bedrock) in production applications.
Work Experience Required: Not explicitly mentioned in the JD.
Experienced in cloud-native engineering with AWS, containers, deployment, observability, and production operations.
Proven ability in technical leadership through architecture decisions and guiding engineering teams in AI initiatives.
Comfortable working with AI engineering patterns such as prompt engineering, tool calling, retrieval, agentic workflows, and evaluation/monitoring of LLM-powered systems.