AI Engineer @ RemoDevs

About Us

We build B2B legal technology that helps law firms and fund managers work faster and with higher quality. Our main product, our platform, makes legal work for raising private investment funds easier. It helps lawyers speed up drafting, negotiation, and compliance at scale.

We run a single-tenant SaaS system on AWS in different regions. Our tech stack includes Python / Django 4.2, React 18 / TypeScript, PostgreSQL, Redis, Elasticsearch / OpenSearch, S3, ECS, and Lambda. Our teams work in Agile Scrum with strong CI / CD, IaC (Terraform / Terragrunt), and security-first practices (SOPS, KMS).

Role Overview

We are looking for a  Mid–Senior AI Engineer  to join our product team and lead AI features in our platform. This is a hands-on role focused on natural language processing (NLP), machine learning (ML), and large language models (LLMs) in production SaaS at scale.

You will design and build models to improve legal document understanding and automate workflows. The solutions must be fast, reliable, and safe for production use in the cloud.

Key Responsibilities

• Research, design, and build NLP and ML models for document parsing, search, classification, and summarization.
• Add LLMs into main product workflows, making sure they are reliable, performant, and safe.
• Work with engineers, product managers, and QA to deliver AI features that meet client needs.
• Improve model serving and inference for low latency and cost in AWS (ECS, Lambda, S3, CloudWatch).
• Build data pipelines for training and testing using PostgreSQL, Redis, Elasticsearch / OpenSearch, and S3.
• Ensure models meet security, compliance, and scale needs for enterprise SaaS.
• Stay up to date with new NLP, LLM, and ML research and bring useful ideas to production.
• Contribute to documentation, code reviews, and knowledge sharing in the engineering team.

Essential Requirements

Preferred Requirements

Personal Attributes

What We Offer

This senior role is a chance to shape the future of our platform — working across the stack to deliver innovative features for leading law firms worldwide.

About Us

We build B2B legal technology that helps law firms and fund managers work faster and with higher quality. Our main product, our platform, makes legal work for raising private investment funds easier. It helps lawyers speed up drafting, negotiation, and compliance at scale.

We run a single-tenant SaaS system on AWS in different regions. Our tech stack includes Python / Django 4.2, React 18 / TypeScript, PostgreSQL, Redis, Elasticsearch / OpenSearch, S3, ECS, and Lambda. Our teams work in Agile Scrum with strong CI / CD, IaC (Terraform / Terragrunt), and security-first practices (SOPS, KMS).

Role Overview

We are looking for a  Mid–Senior AI Engineer  to join our product team and lead AI features in our platform. This is a hands-on role focused on natural language processing (NLP), machine learning (ML), and large language models (LLMs) in production SaaS at scale.

You will design and build models to improve legal document understanding and automate workflows. The solutions must be fast, reliable, and safe for production use in the cloud.

Key Responsibilities

Essential Requirements

Preferred Requirements

Personal Attributes

What We Offer

This senior role is a chance to shape the future of our platform — working across the stack to deliver innovative features for leading law firms worldwide.

,[Research, design, and build NLP and ML models for document parsing, search, classification, and summarization., Add LLMs into main product workflows, making sure they are reliable, performant, and safe., Work with engineers, product managers, and QA to deliver AI features that meet client needs., Improve model serving and inference for low latency and cost in AWS (ECS, Lambda, S3, CloudWatch)., Build data pipelines for training and testing using PostgreSQL, Redis, Elasticsearch / OpenSearch, and S3., Ensure models meet security, compliance, and scale needs for enterprise SaaS., Stay up to date with new NLP, LLM, and ML research and bring useful ideas to production., Contribute to documentation, code reviews, and knowledge sharing in the engineering team.] Requirements : Python, Machine learning, NLP