Overview

More than a mission, C2FO is a better financial system changing the way every business gains access to the working capital they need to thrive.

Responsibilities

• We are looking for an Engineer/Data Scientist to lead the identification and rapid prototyping of AI solutions across our business — spanning both internal operations and customer-facing products.
• Once a prototype is approved, you will work in close collaboration with the rest of the AI Platform Engineering team to translate your work into something that can scale into a production-grade application. You will not co-own productionisation and you will be a critical partner in making it successful.
• This is a role for someone who is energised by ambiguity, moves fast without cutting corners, and knows how to make a compelling case for (or against) a technical approach based on evidence rather than enthusiasm.
• Business Discovery Run structured discovery sessions with department heads and product owners to identify and scope AI opportunities. Define a clear problem statement — including data availability and constraints — before any prototyping begins.
• Rapid Prototyping Build functional POCs using the most appropriate approach for the problem: RAG pipelines, agentic workflows, predictive ML models, or rule-based systems. Prototypes must be credible enough to support a genuine build-or-not decision.
• Stakeholder Management Act as the primary technical point of contact for business stakeholders throughout discovery and POC. Communicate trade-offs around accuracy, cost, and latency in plain terms — and be willing to recommend against building when the evidence calls for it.
• Evaluation & Validation Define success criteria before building begins. Design and run evaluations appropriate to the POC type, and present findings clearly enough for a non-technical sponsor to make a confident go/no-go decision.
• Technical Handoff Produce handoff documentation covering system design, prompt strategies, data requirements, known failure modes, and evaluation benchmarks — giving the AI Engineering team everything needed to take a validated POC into production.
• Proficiency in Python as the primary language for data science and ML development (Pandas, NumPy, Scikit-learn)
• Familiarity with SQL for data querying and manipulation across modern data warehouses (e.g., BigQuery, Snowflake, PostgreSQL)
• (Nice to have) Working knowledge of deep learning frameworks such as PyTorch or TensorFlow for model experimentation
• Hands-on experience working with large language model APIs, including providers such as OpenAI, Anthropic, or Google
• Strong command of prompt engineering techniques, including few-shot prompting, chain-of-thought reasoning, and structured output design
• Experience with open-source LLMs (e.g., Mistral, LLaMA) and an understanding of when to apply open vs. proprietary models
• Practical experience building RAG (Retrieval-Augmented Generation) pipelines, including chunking strategies, embedding models, and retrieval tuning
• Familiarity with agentic orchestration frameworks such as LangChain, LangGraph, LlamaIndex, CrewAI, or AutoGen
• Experience integrating vector databases (e.g., pgvector, Pinecone, Weaviate, ChromaDB) into search and retrieval workflows
• Understanding of tool/function calling patterns for LLM-driven automation
• Ability to define and implement "good enough" metrics and evaluation frameworks for POC validation
• Experience with LLM evaluation libraries such as RAGAS, TruLens, or DeepEval
• Familiarity with experiment tracking tools such as MLflow or Weights & Biases
• Comfort with cost and latency profiling of LLM-based systems to inform feasibility decisions
• Comfortable working within cloud environments (AWS, GCP, or Azure) for data access, compute, and API integration
• Ability to integrate with REST APIs and third-party data sources during prototyping
• Proficiency with standard development tools: Git, Jupyter notebooks, VS Code
• Basic familiarity with Docker for packaging and sharing POC environments with engineering teams

Qualifications

• Location: REMOTE
• 4+ years of experience in data science, machine learning, or a closely related field, with a demonstrated track record of delivering end-to-end projects
• 2+ years of hands-on experience working with large language models or Generative AI solutions in a professional setting
• Proven experience taking projects from business problem discovery through to a working prototype or proof of concept
• Experience engaging directly with non-technical business stakeholders to gather requirements, set expectations, and communicate results clearly
• Strong background in traditional ML approaches (classification, regression, clustering, NLP) alongside modern LLM-based methods

Nice to have

• Experience with fine-tuning or instruction-tuning LLMs on domain-specific datasets
• Familiarity with responsible AI principles, including bias detection, fairness evaluation, and model transparency
• Prior experience in a consulting, pre-sales engineering, or business-facing technical role
• Knowledge of business process mapping (e.g., BPMN) to support structured discovery sessions

Education

• Bachelor's degree in Computer Science, Statistics, Mathematics, Engineering, or a related quantitative field
• A Master's or PhD is a plus, though equivalent industry experience is equally valued
• Ability to translate complex technical outputs into clear business value — you are as comfortable in a boardroom as you are in a notebook
• Strong stakeholder management skills, including the ability to set realistic expectations around LLM capabilities, limitations, and cost trade-offs
• Excellent written communication skills for documenting prompt strategies, data requirements, and POC logic to enable clean technical handoffs
• Self-directed with a high tolerance for ambiguity — you are energised by open-ended discovery, not slowed down by it
• Structured thinker who can design evaluation criteria and define what "success" looks like before building begins

Benefits

• At C2FO, we take care of our customers and our people – the vital human capital that helps our customers thrive. That’s why we offer a comprehensive benefits package, flexible work options for work/life balance, volunteer time off, and more. Learn more about our benefits here. (https://www.c2fo.com/amer/us/en-us/about-us/careers
• Designation: Applied AI Engineer, GenAI and ML Prototyping