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Cracked Software Engineer - Special Projects at HeyMilo AI
Toronto, Ontario, Canada -
Full Time

Start Date

Immediate

Expiry Date

11 Jul, 26

Salary

0.0

Posted On

12 Apr, 26

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

No

Skills

Python, TypeScript, LLMs, Prompt engineering, Cursor, Claude Code, Codex, Databases, APIs, System design, Full-stack development, Conversational AI, Telephony systems

Industry

Software Development

Description
About HeyMilo HeyMilo is building AI interviewers that run real conversations with candidates. We help companies screen faster and make better hiring decisions using conversational AI. We’re a small, fast-moving team working directly with customers on real problems. The Role We’re hiring a cracked software engineer to work on special projects. This is a high-ownership role where you’ll solve ambiguous, real-world problems and ship quickly. You’ll operate across product and engineering, building end-to-end solutions that actually get used. What you’ll do Build and ship full-stack solutions quickly Prototype new AI-driven features and workflows Turn ambiguous requirements into working systems Iterate fast based on real usage and feedback Make pragmatic tradeoffs to move fast What we’re looking for Strong full-stack or backend experience (Python, TypeScript, etc.) Experience with LLMs and prompt engineering Heavy user of AI coding tools (Cursor, Claude Code, Codex, etc.) Strong fundamentals (databases, APIs, system design) Ability to break down complex problems into simple solutions High ownership, scrappy, and execution-focused Comfortable working under pressure and hitting tight deadlines Bonus Experience with conversational AI or telephony systems Experience building production AI systems Why join High ownership and fast iteration Work on real problems with real users Small team, no bureaucracy Work on high-impact problems across customers and product Competitive pay, benefits, and RRSP match
Responsibilities
You will build and ship full-stack solutions while prototyping new AI-driven features and workflows. The role involves turning ambiguous requirements into working systems and iterating rapidly based on user feedback.