You will join the Content Engineering team, specializing in large-scale content processing using cutting-edge technologies. You will leverage AI applications such as NLP and LLMs for document understanding, including document classification, text categorization, data extraction, and semantic similarity. You'll deploy production-grade LLM solutions, fine-tune state-of-the-art LLMs for specialized data extraction tasks, and develop prompt engineering strategies to maximize reliability and performance on confidential business documents. You'll tackle engineering challenges like high latency and non-deterministic output, implement pipelines that process high volumes of complex documents accurately and efficiently, integrate LLM observability tools to trace and monitor extractions, and own systems end-to-end including design, coding, monitoring, testing, CI/CD, and on-call support.
Responsibilities
- Deploy LLM based production grade solutions
- Fine-tune and adapt state of the art LLMs for specialized data extraction tasks
- Develop innovative prompt engineering strategy and systems to maximize reliability and performance on confidential business documents
- Solve engineering challenges that come along with LLM solutions, such as high latency and non-deterministic output
- Implement and scale data processing pipelines that can process high volumes of complex documents with high accuracy and efficiency
- Integrate and manage LLM observability to trace debug and monitor every extraction
- Own systems end-to-end including designing coding monitoring testing CI/CD and on-call support
Requirements
- 4+ years of experience as a software engineer, primarily with Python
- Advanced degree (Bachelor's / Master's) in Computer Science, Computer Engineering, or a relevant field with a focus on Artificial Intelligence, machine learning, or equivalent industry experience
- 2+ years of hands-on experience building and deploying applications that use Large Language Models (LLMs)
- Experience in extracting structured JSON from text using LLMs and a deep understanding of Prompt Engineering
- Proficiency in classic NLP libraries for tasks like NER, text classification, and pre-processing
- Experience with LLM tracing, debugging and evaluation platforms such as Langfuse
- Excellent communication, organizational, problem-solving, debugging, and analytical skills
- Experience in async processing of data at scale
- Using frameworks like LangChain, HuggingFace, and backend web frameworks like FastAPI
- Expertise on core engineering skills - Cloud, microservice architecture, caching, and queuing
- Familiarity with concepts/tools as Docker, k8s, VCS, CI/CD
- Previous experience in data extraction from specific domains (e.g., financial reports, news)