About the Company
Our client is a fintech and data technology company helping organizations embed financial services into everyday business experiences. Its mission is to reinvent finance as a service by combining modern financial infrastructure, alternative data, and generative AI.
The company supports digital transformation across financial institutions and large enterprises, developing solutions that improve decision-making, automate business processes, and make complex data more accessible. Its work spans AI-powered business systems, data platforms, enterprise collaboration tools, and industry-specific applications.
Employees join a collaborative, intellectually curious environment where engineers are encouraged to take ownership, learn continuously, and contribute beyond narrowly defined responsibilities. The company offers the opportunity to work on meaningful products at the intersection of finance, data, and AI while helping shape the next generation of intelligent business infrastructure.
What the Job Entails
As an AI Full-Cycle Engineer, you will design, develop, and operate products and data systems that use large language models and generative AI to solve real business challenges. Your assignment will be determined in discussion with you based on your experience and interests.
You may work on financial research services, enterprise data platforms, real estate applications, AI-powered decision-support systems, or infrastructure for governed AI agents. Responsibilities may include building data pipelines that combine scraping, OCR, and LLMs; extracting and structuring information from unstructured documents; developing AI-enabled business systems; improving model accuracy; and creating monitoring and quality-assurance frameworks.
You will work across the product lifecycle, from research and prototyping through implementation and operation. Success in this role requires a customer-focused mindset, strong ownership, attention to data quality, and the ability to involve colleagues and move projects forward collaboratively.
Key Requirements
Professional software development experience using one or more programming languages.
Hands-on experience developing products or systems that use generative AI or large language models.
Experience using SaaS products or services related to generative AI or LLMs.
Practical knowledge of prompt engineering, context engineering, or other approaches to improving LLM performance.
Experience with LLM evaluation, benchmarking, fine-tuning, or quality monitoring.
Basic knowledge and practical experience in natural language processing or machine learning.
Experience designing and developing data engineering or ETL processes.
Experience building infrastructure on cloud platforms such as AWS.
Experience with infrastructure as code tools such as Terraform.
Experience developing or operating container-based applications.
Knowledge of database, network, or application performance tuning.
Understanding of secure coding practices.
Conversational English sufficient to collaborate with international engineering teams.
A customer-centric approach and the ability to determine priorities based on user value.
Strong ownership, intellectual curiosity, attention to detail, and the ability to collaborate effectively across teams.