AI Engineer — Kudwa (via Remotesome)

About Kudwa

Kudwa is a pioneering CFO tech platform revolutionizing the way businesses make financial decisions. Utilizing advanced AI and expert CFO insights, our software empowers companies with accurate, actionable data, aiding them in making swift, intelligent choices. Our platform excels in merging financial data to offer clear visualizations of crucial performance metrics and predictive business trajectories. Additionally, Kudwa offers fractional CFO services, helping businesses not only construct robust financial frameworks but also strategically align with the most effective KPIs for enduring growth.

What You’ll Do

1. Build and Deploy AI-Powered Features

• Develop and train machine learning models tailored to finance use cases (e.g., forecasting, anomaly detection, recommendation engines).

• Experiment with LLMs and other generative AI APIs to enhance user experience and automate workflows.

• Contribute to the full lifecycle of models—from ideation and prototyping to deployment and monitoring.

2. Work Across a Modern AI Tech Stack

• Core: Python

• Data: SQL, PostgreSQL, ETL pipelines

• Tools: OpenAI APIs, Anthropic APIs, Weights & Biases, Hugging Face

• Collaborate with backend engineers to integrate AI features into our Node.js-based platform.

3. Learn and Grow with the Team

• Work closely with our AI and product teams to scope meaningful experiments.

• Review data quality, build pipelines, and learn to apply AI responsibly in production settings.

• Learn best practices in MLOps, model evaluation, and performance tracking.

4. Collaborate Beyond the Model

• Partner with engineers, designers, and fractional CFOs to translate business needs into intelligent systems.

• Discuss UX behavior that results from AI decisions and outputs.

• Support the documentation of AI features and decision paths for transparency and maintainability.

5. Help Keep AI Reliable and Accountable

• Monitor deployed models and retrain or tune them as data evolves.

• Set up testing, fallback logic, and explainability frameworks where needed.

• Track model drift and validate predictions against live business data.

What You’ll Bring

• 1–2 years of hands-on experience building or deploying AI/ML systems.

• Strong proficiency in Python, with a good grasp of data structures, modeling techniques, and APIs.

• Experience working with structured datasets, feature engineering, and basic model evaluation.

• Curiosity about financial systems and how AI can enhance decision-making.

• A collaborative mindset—you ask great questions, seek feedback, and love learning from others.

• A high sense of ownership when taking on a task, autonomous working with minimal oversight.

• Bonus: familiarity with LLMs, vector databases, financial forecasting models, or time-series data.

Nice To Have

• Familiarity with financial reporting concepts (e.g., P&L, balance sheets, cash flow).

• Experience using OpenAI, Anthropic, or Retrieval-Augmented Generation (RAG) workflows.

• Exposure to tools like FastAPI, Docker, or cloud ML services (AWS/GCP/Azure).

Required Skills

• Python — Advanced
• Open AI API — Advanced
• Anthropic API — Advanced
• Weights & Bases — Advanced
• Hugging Face — Advanced
• RAG Workflows — Nice to have
• FastAPI — Nice to have
• Cloud ML Services — Nice to have

Compensation

$60K – $80K/year

Timezone: UTC-8 to UTC-3