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Business Process Analyst / Business Process Engineer (Gen AI )

Zero Cognitive Systems, Inc.

Business Process Analyst / Business Process Engineer (Gen AI )

Campbell, CA
Full Time
Paid
  • Responsibilities

    Zero Systems, a VC-backed AI startup headquartered in Silicon Valley, California is seeking an experienced Business Process Analyst/Engineer.

    ZERO offers an operating and orchestration system for building, deploying, and maintaining AI applications for large enterprises. Using ZERO, enterprises increase revenue, improve profitability, and enhance worker satisfaction.

    Job Responsibilities

    • Develop complex process maps and related business process artifacts that provide end-to-end view of cross functional practices and LOBs.

    • Identify process health, flag significant process breakdowns and gaps, incomplete handoffs or missing boundary processes.

    • Use analytics and quantitative methods to assess business process flows with a focus on automation and annotation.

    • Client facing, work with customers to validate business process mapping and diagrams.

    • Decompose process into atomic steps end-to-end.

    • Inspect all samples of customer provided documents and create initial annotations for entities and rules with all data (entities and rules) identified and documented.

    • Work with AI Engineers to validate annotations.

    • Extract additional context as needed from recorded meetings and use for fine-tuning.

    • Provide clarification to Annotators as needed.

    • Work with AI Engineering to use Python scripts to run prompts against several LLMs and document results. Identify the prompts with the best outcomes and results.

    Key Expectations

    • Business process flow diagrams, maps, etc.

    • Business process decision tree with detailed data elements and identified gaps.

    • Prompt engineering tasks.

    • Initiate the annotation and provide guidelines to the annotation team.

    Role Skills

    • Business process diagramming and documenting expertise.

    • Generative AI knowledge and experience

    • Process engineering (data attributes) and annotation within NLP.

    • Experience with a variety of LLMs.

    • An understanding of core prompt engineering steps.

    • Communication and product development steps.

    • Technical acumen: how business translates into realistic AI skills.