Senior Python / AI /LLM in Production Engineer
Improving · Remote
Skills in this posting
The posting
7+ years of software development experience, with demonstrated experience building production systems.
Strong experience with Python and backend software development.
Experience building Python-based document processing pipelines , including parsing, transformation, and metadata extraction.
Hands-on experience integrating and orchestrating Large Language Models (LLMs) within production applications.
Experience with prompt engineering , including designing, tuning, and evaluating prompts for information extraction, classification, and document processing workflows.
Experience building web applications and REST APIs .
Experience developing AI-powered applications using LLMs .
Familiarity with XML, XHTML, and data transformation pipelines .
Strong problem-solving skills and comfort working with ambiguity in early-stage products.
Excellent communication and collaboration skills.
Drive the production hardening of the current proof-of-concept, including code quality, performance optimization, scalability, and reliability improvements.
Establish foundational infrastructure and architectural patterns, including pipeline architecture, logging, configuration management, and error handling.
Build and maintain Python-based backend services and REST APIs supporting the AI tagging workflow.
Develop and evolve the web user interface, ensuring usability and alignment with engineering standards.
Build document processing pipelines for structured and semi-structured documents, including parsing, transformation, and metadata extraction.
Work with XML and XHTML processing to handle input data and generate compliant XBRL packages.
Integrate and orchestrate Large Language Models within production applications, including prompt engineering, workflow orchestration, error handling, and result evaluation.
Collaborate with the R&D team to understand AI tagging improvements and translate them into engineering requirements.
Participate in code reviews, architecture discussions, technical design, and production support.
Work closely with cross-functional teams to troubleshoot issues and continuously improve the platform.
Success in this role will be measured by the ability to help transition the existing proof-of-concept into a reliable, scalable production platform while improving performance and significantly reducing manual tagging effort.
Experience with XBRL , financial compliance, regulatory reporting, or financial data processing.
Knowledge of investment company operations and SEC filing requirements .
Familiarity with Retrieval Augmented Generation (RAG) , embeddings, vector databases, or semantic search.
Familiarity with modern web frameworks and full-stack development, particularly React, TypeScript, JavaScript, FastAPI, or Flask .
Experience with LLM platforms or frameworks such as OpenAI, Azure OpenAI, Anthropic, LangChain, LangGraph, or LlamaIndex .
Experience scaling systems and performing performance optimization.
Background in document intelligence, NLP, information extraction, or classification systems.
Experience in financial services, investment management, or regulatory technology.
Comprehensive medical, dental, vision, and life insurance
Mental health support
Savings Fund & Corporate Retirement Plan
Paid time off, vacation bonus, and Christmas bonus
Career development, certifications, and continuous learning
TotalPass wellness program
Collaborative culture with internal events and technical communities
Opportunity to work on innovative global projects with cutting-edge technologies
The PivotHop read
- What an industrial engineer actually earnsmedian, seniority, by country
- Where industrial engineers move nextevery measured route out
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Where these skills also reach
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