JOB DESCRIPTION

Designation: Prompt Engineer

Location: Hyderabad

Work Mode: Work From Office

About US:

Foundation AI automatically ingests incoming documents, emails, and attachments from across your firm. It profiles matches, classifies, and saves each to your DMS, and then automates document-dependent workflows according to your rules. Read more about us at www.foundationai.com

Job Summary:

As a Prompt Engineer within the Data Science function, you will be at the forefront of designing and optimizing prompt strategies to facilitate automation and enhance document processing efficiency. You will design, test, and deploy prompts that power AI-driven workflows, collaborating closely with data scientists, product teams, and software engineers to deliver high-impact solutions.

If working in a fast-growing environment, tackling complex challenges, and making a significant impact excites you, then you’re the right fit for this role.

Key Responsibilities:

1. Prompt Design and Optimization:

• Develop, refine, and optimize prompts for large language models (LLMs) to improve accuracy and efficiency in document processing and automation workflows.
• Develop and implement templatized prompt frameworks to ensure scalability and adaptability across various industries, domains, and use cases.
• Conduct extensive A/B testing of prompts to identify the most effective language constructs and structures.
• Apply data science methodologies to evaluate prompt performance, ensuring accuracy, relevance, and efficiency.
• Continuously refine prompts to adapt to changing data patterns and use cases.

2. Collaboration and Cross-Functional Support

• Support Data Scientists in research initiatives and ML Engineers in identifying tools, building, and improving frameworks for the prompt lifecycle.
• Work closely with data scientists, NLP specialists, and software engineers to integrate optimized prompts into production workflows.
• Collaborate with product and engineering teams to understand user requirements and design language models accordingly.
• Provide prompt engineering expertise to customer success and delivery teams for customized solutions.

3. Data-Driven Performance Analysis

• Set up metrics for evaluation and establish ground truth to define success criteria and identify areas for improvement.
• Analyze prompt performance using quantitative metrics, including accuracy, relevance, and execution time.
• Develop dashboards and reporting tools to track prompt efficacy and inform strategic decisions.
• Conduct post-deployment analyses to evaluate real-world performance and make data-driven improvements.

4. Research and Innovation

• Prepare benchmark evaluation datasets to support data science algorithms and prompt performance testing.
• Stay up-to-date with advancements in NLP and prompt engineering methodologies, leveraging the latest research to improve prompt efficiency.
• Prototype and experiment with new prompt strategies, contributing to innovation in AI-driven document processing.

5. Quality Assurance and Compliance

• Implement rigorous testing frameworks to ensure prompt reliability and performance in diverse scenarios.
• Maintain compliance with data governance standards and security protocols, ensuring that prompts meet organizational and regulatory requirements.

Required Qualifications:

Education:

Bachelor’s or Master’s degree in Data Science, Computer Science, Artificial Intelligence, Computational Linguistics, or a closely related field.

Experience:

3+ years of experience in NLP, machine learning, or data science, with a strong focus on prompt engineering or LLM optimization.

Hands-on experience with prompt generation, updates, optimization, feedback loop, and reporting for various LLMs (e.g., OpenAI, Gemini, etc.).

Proven track record of deploying prompt-driven solutions in production environments.

Experience with data privacy and compliance in AI applications, including familiarity with GDPR and other relevant data protection regulations.

Technical Skills:

Familiarity with prompt lifecycle management tools such as Agenta, Langfuse, and LangChain for efficient monitoring, iteration, and optimization of prompt performance.

Expertise with LLM prompt engineering techniques, including few-shot, zero-shot, and fine-tuning methodologies.

Proficiency with Python and familiarity with prompt engineering tools, libraries, and frameworks commonly used for working with LLMs, such as OpenAI API, Hugging Face Transformers, LangChain, or similar technologies.

Experience with data analysis using Pandas, NumPy, and visualization tools like Matplotlib or Seaborn.

Soft Skills:

Problem-Solving: Demonstrated ability to develop creative solutions to NLP challenges.

Communication: Strong written and verbal communication skills, with the ability to present technical concepts to non-technical stakeholders.

Collaboration: Experience working in cross-functional teams with a focus on delivering user-centric solutions.

Nice-to-Have:

Familiarity with industry-specific terminology and domain knowledge, particularly in legal, healthcare, insurance, and paralegal contexts, to enhance prompt accuracy and contextual relevance.

Familiarity with data labeling tools and annotation workflows.

Publications or contributions to open-source projects related to NLP.

Knowledge of cloud-based AI platforms (AWS, GCP, Azure) is a plus.

For any feedback or inquiries, please contact us at careers@foundationai.com

Learn more about us at www.foundationai.com