- Work with the Founders and Product Team to understand use-cases, business rules, and data pipelines.

- Define AI workflows for compensation planning, analytics, and recommendations.

LLM Selection & Customization :

- Evaluate open-source and commercial models (e.g., GPT, LLaMA, Gemini, Claude).

- Select an appropriate base LLM based on performance, cost, licensing, and scalability.

- Fine-tune model(s) using domain-specific data (survey data, HR data, compensation logic).

API Development :

- Fine-tuning process management.

- Prompting & query handling.

- Response generation with structured outputs for consumption.

- Ensure APIs are secure, well-documented, and scalable.

LLM Finetuning Workflow :

- Research and recommend workflow editing/orchestration libraries (e.g., Temporal.io, Camunda, n8n, Node-RED, Dagster, Airflow, LangFlow).

- Benchmark usability for low-code/no-code rule builder capabilities so pay policies and comp rules can be modeled and adjusted by HR/business users.

- Integrate chosen library into architecture for seamless interaction with AI/ML models and business logic.

Cost and Performance Monitoring :

- Support the practice for set up monitoring, logging, and usage analytics for performance tuning.

- Ensure data security, compliance, and cost optimization.