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Mid-level generalist title, metro location, and 3-6 year experience amplify competition.
Specialized LLM/NLP skills are transferable but domain-specific extraction experience favors finance/news backgrounds.
Explicit years, mandatory Python and LLM experience, and required production LLM skills heighten filter.
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Deploy and maintain production-grade LLM-based solutions for specialized data extraction and document understanding.
Fine-tune LLMs and develop prompt engineering strategies to enhance reliability and performance on confidential business documents.
Design, build, and scale high-throughput data processing pipelines, including end-to-end responsibility such as coding, monitoring, testing, CI/CD, and on-call support.
Minimum 4 years software engineering experience primarily using Python.
At least 2 years hands-on experience building and deploying applications using Large Language Models (LLMs).
Understanding and experience in prompt engineering and extracting structured JSON outputs from text with LLMs.
Bachelor's/Master's degree in Computer Science, Computer Engineering, or related AI/ML field or equivalent industry experience.
Experienced in NLP and state-of-the-art LLM technologies with a strong focus on building production AI solutions.
Comfortable owning full engineering lifecycle including design, deployment, monitoring, and on-call support in scalable environments.
Skilled in debugging, tracing, and evaluating LLM performance using platforms like Langfuse and familiar with prompt engineering and LLM observability tools.