AI Browser Automation Specialist

We're looking for a specialist to extend our existing browser extension with intelligent auto form-fill capabilities. The feature fills lender application forms on third-party websites using data from our platform — automatically, reliably, and fast.
This role sits at the intersection of browser extension development, DOM engineering, and applied AI. You'll be solving real-world messiness: forms that change without notice, validation rules that differ from what our data provides, and multi-step flows that need to navigate themselves.

What You'll BuildWorking within our existing extension codebase, you'll implement a form-fill feature that:

• Reads structured applicant data already captured by the extension from our platform

• Automatically fills multi-step lender application forms (e.g. credit application portals)

• Navigates between form steps autonomously

• Detects and self-corrects validation errors — including fuzzy data mismatches between our platform data and what the form expects (e.g. date formats, field length constraints, dropdown option matching)

• Self-heals when form structure changes — using AI to adapt to minor DOM shifts (renamed fields, reordered steps, changed selectors) without code changes. Significant structural overhauls (full page redesigns, new multi-step flows) may require a targeted code update, but the goal is to minimise how often that's needed.

• Prioritises speed: static DOM injection for known fields, AI only where it adds value (error correction, unknown fields, structural changes)
  

Technical Requirements

• Solid experience contributing to existing browser extension codebases (Chrome/Manifest V3)

• Deep knowledge of DOM manipulation, form interaction, and event simulation — including framework-controlled fields (React, Vue, Angular)

• Able to design hybrid pipelines: fast static fill for the happy path, AI fallback for edge cases

• Practical experience integrating LLM APIs (OpenAI, Anthropic, or similar) into production features

• Understanding of form validation patterns and how to detect and respond to them programmatically
  

Nice to Have

• Experience with self-healing selector strategies (semantic fallbacks, selector scoring, visual anchoring)

• Prior work on form automation across multiple third-party portals (fintech, insurance, automotive lending)

• Familiarity with prompt engineering for structured data correction tasks

• Experience working in codebases that mix static automation with AI-assisted fallback logic
  

What Success Looks Like

• Form fill completes end-to-end without human intervention on the majority of submissions

• AI-assisted error correction handles common data mismatches automatically

• When a lender updates their form, the system degrades gracefully and self-corrects rather than silently failing

• Fill speed is not noticeably impacted by AI calls — AI runs only on failure paths or where static fill isn't sufficient

Engagement

• [Contract / Full-time — adjust as needed]

• Opportunity for full time role applies.

• Remote-friendly. Must be able to collaborate async with our engineering team.