Founding Applied AI/ML Engineer

Cora AI, Inc.; Los Angeles (CA); Remote; USD 120,000 - 150,000; Full time

Job summary

A B2B technology company is seeking an experienced ML Engineer to design and implement AI agent architecture. The ideal candidate has over 5 years of ML engineering experience and a strong background in LLM frameworks. This role offers significant influence over the product roadmap and culture, with a remote-friendly working model.

Qualifications

• 5+ years of production ML engineering experience.
• Strong expertise in modern LLM frameworks and RAG architectures.
• Experience building and deploying production AI systems.

Responsibilities

• Design and implement core AI agent architecture.
• Build and optimize RAG pipelines for knowledge integration.
• Develop contextual memory and knowledge graph systems.

Skills

Production ML engineering experience

Expertise in modern LLM frameworks

Natural language processing

Education

Bachelor's or Master's in Computer Science/Engineering

Tools

Python with FastAPI

PostgreSQL

React

Job description

Overview

At Cora AI, we’re reimagining how B2B companies engage and delight their customers. We’re harnessing AI agents to rebuild customer operations from the ground up, orchestrating a blend of digital and human touchpoints to enable high-touch service at scale while making customer relationships feel more human than ever.

Our founding team brings deep expertise in generative AI and automation platforms, with backing from investors and executives from LinkedIn, BetterUp, Glean, Scale AI, and Gusto. We’re on a mission to transform enterprise customer experiences in the age of AI.

The Role

As one of our first engineering hires, you will work directly with our technical co-founder to architect and build Cora from the ground up. You’ll have significant influence over our roadmap and help establish our engineering culture.

What You’ll Do

• Design and implement our core AI agent architecture and orchestration systems
• Build and optimize RAG pipelines for enterprise knowledge integration
• Develop contextual memory and knowledge graph systems that learn from every interaction
• Create AI observability and quality monitoring systems
• Build predictive models for customer health, churn risk, and growth opportunities
• Implement sentiment analysis and intent detection systems
• Design feedback loops that continuously improve our AI's performance

Requirements

• Bachelor's or Master's in Computer Science/Engineering or equivalent experience
• 5+ years of production ML engineering experience
• Strong expertise in modern LLM frameworks and RAG architectures
• Experience building and deploying production AI systems
• Experience with conversation AI and natural language processing
• Deep understanding of LLMOps and AI observability

What Sets You Apart

• Ability to navigate ambiguity & challenges with composure
• Strong sense of ownership and reliability
• Insatiable curiosity and passion for learning
• Early adopter mindset — you're already using AI tools like Cursor to be a 100x developer
• Responsive to feedback and quick to implement improvements
• Autonomous work style while being excellent at collaboration
• Natural mentorship abilities and a team-first mindset
• Experience in fast-paced startup environments

Our Tech Stack

We've built a tech stack optimized for developer experience and rapid iteration, prioritizing fast feedback loops and maintainable code with thorough test coverage and modern CI/CD practices.

• Backend: Python with FastAPI, SQLModel and Celery
• Persistence: PostgreSQL with pgvector and Redis
• Frontend: React and Vite
• AI: Agno and LangGraph
• Observability: BetterStack and Langfuse
• Note: Our stack will evolve with input as the product evolves

To Apply

SF Bay Area, USA (Remote)

About Us

We are reimagining how B2B companies engage and delight their customers. We aim to orchestrate the perfect blend of digital and human touchpoints, enabling high-touch service at scale while keeping relationships human. Our team includes founders and executives from LinkedIn, BetterUp, Glean, Scale AI, and Gusto, and investors from Acrew Capital, Emerson Collective, and Recall Capital.