Finviz is a leading stock screening platform with a strong presence in the American market, serving 3 million monthly visitors. Our platform is trusted and regularly used by professionals from leading financial institutions—such as HSBC, Goldman Sachs, and Bank of America—as well as by enthusiastic beginners. With an international team across the United States, Slovakia, and the Czech Republic, we’re building tools that make a real impact.
As an AI Engineer (LLM/Agents), you’ll play a key role in building a new Finviz sub-product that delivers AI-driven analysis of financial markets and world news—putting information into context for investors to augment decision-making.
Responsibilities
- Design and implement LLM-powered features for market/news understanding: summarization, extraction, classification, and contextual “what matters and why” investor narratives.
- Build agentic workflows (multi-step reasoning + tool use) that reliably gather evidence, run checks, and produce grounded outputs.
- Own model selection and routing: choose the right model per task based on quality, latency, and cost; implement fallbacks and safe degradation.
- Implement tool/function calling patterns to connect LLMs to Finviz data, internal services, and external signals (schemas, constraints, validation, error handling).
- Write and maintain production-ready prompting assets: guidelines, rubrics, templates, and “agent skills” for consistent behavior across workflows.
- Build evaluation pipelines (offline + online): golden sets, regression tests, A/B experiments, and quality metrics tied to product outcomes.
- Optimize token usage, context strategy, caching, and verbosity control to hit cost/performance targets.
- Collaborate closely with product and engineering to ship fast, iterate, and maintain high reliability.
Requirements
- Strong software engineering fundamentals—you ship production systems, not demos.
- Practical experience integrating LLMs into real products (not “I used ChatGPT”)
- Solid understanding of agent patterns and tool use
- Ability to write clear specifications and guidelines that other engineers (and models) can follow.
- Comfort owning ambiguous problems end-to-end: prototype → production → monitoring → iteration.
- Bonus: interest in finance/markets (we don’t require a deep finance background—curiosity is enough).
Our Tech Stack
- Python for LLM services and orchestration
- Typical components: APIs, queues/workers, caching, observability, eval tooling
- Finviz stack includes React, TypeScript, .NET Core/C#, SQL Server, plus Python/Node.js for specific tasks
Benefits
- Remote-first. Work from anywhere—home, a café, or on the road. Our remote-first approach gives you the freedom to choose where you thrive best.
- Flexible Schedule. You decide when you're at your peak. A flexible schedule lets you balance work with your lifestyle and priorities.
- Competitive Salary. Your work deserves top reward. We offer a competitive salary that reflects your talent and contribution.
- Work Autonomy. We trust you. With work autonomy, you have the space to create, decide, and lead projects your way—your voice matters here.
