Sr Prompt Engineer Remote - Only on W2

  • Posted 2 days ago | Updated 2 days ago

Overview

Remote
$70 - $100
Contract - W2

Skills

Prompt
LLM
GEMINI
ETL
OPENAI
SQL
PYTHON

Job Details

Hi,
Hope you are doing great,
Hiring on Sr Prompt Engineer Remote - Only on W2
EXP: 10+ Required Skills & Qualifications:
  1. Experience with LLMs and Generative AI (OpenAI, Gemini, Claude, or open-source like LLaMA, Mistral).
  2. Strong understanding of SQL and data querying principles.
  3. Knowledge of data workflows including ETL, data validation, and data profiling.
  4. Proficiency in Python for interacting with LLM APIs, prompt chaining, and evaluation scripts.
  5. Familiarity with data modeling and analytics concepts.
  6. Excellent written communication for designing precise, clear prompts.
  7. Ability to evaluate and iterate prompts systematically.

Role Overview:
As a Prompt Engineer Data, you will:

  1. Design, engineer, and optimize prompts for LLMs focused on structured and unstructured data workflows.
  2. Develop reusable prompt libraries for data extraction, transformation, summarization, and QA.
  3. Collaborate with data engineers, data scientists, and product teams to build LLM-powered data agents.
  4. Evaluate prompt effectiveness across accuracy, consistency, and hallucination rates.
  5. Continuously refine prompts using A/B testing and feedback loops to improve response quality on data-centric tasks.

Key Responsibilities: Design high-quality prompts for:
  1. Query generation and validation
  2. Table summarization and trend extraction
  3. Data cleaning, normalization, and mapping tasks
  4. Automated data documentation and metadata extraction
  5. Optimize prompts for cost-efficiency across different LLM providers (OpenAI, Gemini, Claude, open source).
  6. Stay current on LLM advancements and integrate advanced prompting methods (chain-of-thought, tree-of-thought, self-consistency, reflection).
  7. Document prompt engineering guidelines and best practices for internal teams.
  8. Collaborate with MLOps/DevOps teams to deploy prompt-driven pipelines into production reliably.
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