Remote AI Lead Engineer — Fintech Platform

Openkrill

United States

Remote

USD 100,000 - 120,000

Full time

10 days ago
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Benefits offered by this job

Equity opportunities
Unlimited PTO
Learning & development stipend
Fully remote

Job summary

Alternative Payments is building a financial operating system for SMBs, expanding AI-powered analytics and payments capabilities. We’re seeking a Lead Software Engineer to set the technical direction of Alti, our AI agent product, remote from Brazil.

You’ll own technical decisions, define evaluation standards, and lead architecture across LLMs, agents, and proprietary ML models. You’ll write code weekly, collaborate with product teams, and push for production-grade AI features with monitoring

Qualifications

  • Hands-on experience with AI products in production (LLMs, agents, AI features) in the last 12 months.
  • Experience with chatbots, RAG and LLM evaluation pipelines.
  • Strong skills in Go, TypeScript/JavaScript or Python.

Responsibilities

  • Own the technical direction of Alti features, from conversational AI to agents and automated routines.
  • Define the standards for LLM evaluation, prompt management, monitoring and observability.
  • Lead the design of RAG pipelines and agent architectures, and make the trade-off calls.
  • Drive the move from LLM-only features to proprietary ML models, including production with monitoring and continuous feedback.
  • Identify new ML use cases across the AP platform and shape them with Product.
  • Act as a reference for AI inside the product org: review designs, pair with engineers and share practices.
  • Keep shipping hands-on: this role writes code every week.

Skills

AI features
Go
TypeScript
Python
Tech leadership
Product mindset

Job description

Alternative Payments is building a financial operating system for SMBs, expanding AI-powered analytics and payments capabilities. We’re seeking a Lead Software Engineer to set the technical direction of Alti, our AI agent product, remote from Brazil.

You’ll own technical decisions, define evaluation standards, and lead architecture across LLMs, agents, and proprietary ML models. You’ll write code weekly, collaborate with product teams, and push for production-grade AI features with monitoring

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