Responsibilities
- Design and execute the evaluation framework for AI outputs.
- Write and maintain automated test suites for various workflows.
- Set up and enforce quality gates in CI/CD pipelines.
- Produce test artifacts and documentation that meet compliance standards.
- Triage bugs and write reproduction cases for production issues.
Requirements
- Seven or more years in software QA engineering.
- At least two years of experience testing AI or ML systems.
- Proficient in Python and automated testing frameworks like pytest, Playwright, or Selenium.
- Experience building evaluation pipelines for LLM outputs.
- Familiarity with compliance in fintech or regulated environments is a strong advantage.
Benefits
- Competitive base salary and meaningful equity.
- Remote work option within the US.
- Occasional travel to client sites and team offsites.
About Titan AI
Titan isn’t adapting AI to banking. We’re building AI that thinks like a bank. Titan delivers secured, explainable access to both general-purpose LLMs and its own proprietary banking-native AI models purpose-built for the operational, regulatory, and risk realities of financial services through one interface. Additionally, Titan offers Banking Agents that leverage its banking models to deliver industry-leading agentic outcomes. Designed from day one by former bankers, regulators, and AI engineers, our models embed domain expertise directly into their foundation, not as an afterthought. The results speak for themselves: - Blind tested against ChatGPT, Claude, and Gemini - and compliance officers preferred Titan's responses more than 70% of the time on average. - Significant outperformance on banking tasks over common general-purpose LLM - Other advantages related to our ontology, semantic layer, etc., have driven us to become the preferred AI platform for banking Unlike general-purpose LLMs, Titan’s models reason with banking logic, delivering exam-ready, explainable, and auditable outputs, even when data is incomplete or prompts are imperfect. Built on a proprietary banking ontology and evaluated using Titan’s Banker Trust Index (BTI), our models align with how institutions actually operate and how regulators assess decisions. This reduces risk, improves consistency, and increases trust across critical workflows.