Applied AI Engineer

Applied AI Engineer

About the Company
A product-focused AI company building an AI-powered platform to automate loan underwriting. Its AI agents analyse financial and legal documents, helping lenders process more loans with greater accuracy and lower risk.

About the Role
We are looking for an Applied AI Engineer to build and deploy AI agents that analyse complex documents, extract information, identify inconsistencies, and provide evidence-backed answers. The role involves developing AI workflows, backend services, and evaluation systems to ensure accuracy and reliability.

Key Responsibilities

• Build stateful, multi-agent AI workflows using LLMs and Python.
• Develop backend services, APIs, and databases to support AI features.
• Design evaluation frameworks to measure AI accuracy and performance.
• Improve AI systems using production feedback, testing, and error analysis.
• Ensure AI outputs are traceable, auditable, and supported by source evidence.
• Experiment with new AI models and techniques to improve quality, speed, and cost.
• Collaborate with product teams and domain experts to solve real-world lending challenges.

Requirements

• 3+ years of professional software engineering experience, including shipping LLM-based systems to production.
• Strong Python programming skills and hands-on experience building AI agents.
• Understanding of LLMs, embeddings, RAG, and retrieval systems.
• Experience with multi-agent workflows, tool calling, context management, and stateful systems.
• Experience building evaluation datasets, testing AI outputs, and improving system performance.
• Ability to develop backend services, APIs, and databases.
• Familiarity with TypeScript, GraphQL, and PostgreSQL.
• Strong problem-solving skills and the ability to take features from development to production.

Good to Have

• Experience with scanned documents, OCR, tables, and large PDFs.
• Exposure to financial, legal, lending, or insurance documents.
• Experience with model fine-tuning techniques such as LoRA or RLHF/RLAIF.
• Familiarity with DSPy and prompt optimisation.
• Experience working with graph-based data or ownership structures.

Why Join?

• Work on real-world AI products that impact lending decisions.
• Take ownership of features from design to production.
• Collaborate with a product-focused founding team on challenging AI engineering problems.