Sr. AI Engineer (Customer Facing)

RapidCanvas; United States; Remote; USD 140,000 - 190,000; Full time

Benefits offered by this job

Opportunity to help establish a new AI

Job summary

RapidCanvas is seeking an experienced AI/ML engineer to build and deploy production AI applications for enterprise clients. You will translate business needs into working solutions, lead deployment projects, and guide customers and internal teams in using AI tools effectively.

The role requires hands-on experience with language models, scalable backend services, and agent frameworks. You will collaborate with stakeholders to deliver robust AI-powered outcomes and maintain high standards for

Qualifications

• At least five years of hands-on AI/ML engineering or backend systems experience.

Responsibilities

• Understand requirements from customer stakeholders and shape them into scalable AI applications.
• Design and integrate multi-step agents and workflows that automate IT tasks or use operational signals.
• Develop retrieval-augmented generation pipelines grounded in customer knowledge.
• Manage the AI delivery lifecycle from data prep to deployment, monitoring and improvement.
• Coordinate with customer data science and internal teams; share feedback to build better AI solutions.
• Write maintainable Python and apply engineering practices to ensure performance, accuracy and scale.

Skills

Python

Backend services/APIs

Machine learning

Generative AI

LangChain

LangGraph

CrewAI

Pinecone

Weaviate

FAISS

Enterprise stakeholder management

Tools

LangChain

LangGraph

CrewAI

Pinecone

Weaviate

FAISS

Job description

Role overview

Build and deploy production AI applications for enterprise customers, combining applied machine learning with customer-facing technical guidance. You will translate business needs into working solutions, lead projects through deployment and optimization, and help customers and internal teams use AI tools effectively.

Responsibilities

• Work with customer stakeholders to understand requirements and shape them into scalable AI applications.
• Design and integrate multi-step agents, including workflows that automate IT tasks or use operational signals such as logs and APIs.
• Develop retrieval-augmented generation pipelines that ground language model responses in customer-specific knowledge.
• Manage the AI delivery lifecycle, from data preparation and model development through deployment, monitoring, and improvement.
• Coordinate with customer data science teams and internal engineering, product, and solutions groups; share product feedback and help customers build applications.
• Write maintainable Python and apply engineering practices that support performance, accuracy, and scale.

Requirements

• At least five years of hands-on AI/ML engineering or backend systems experience, including recent work with language models or intelligent agents.
• Strong Python skills and experience building scalable backend services or APIs.
• Applied knowledge of machine learning, deep learning, and generative AI, with hands-on experience using language model platforms.
• Practical experience with agent frameworks such as LangChain, LangGraph, or CrewAI, and vector databases such as Pinecone, Weaviate, or FAISS.
• Experience working with enterprise stakeholders, presenting technical work, managing multiple projects, and operating independently.

Nice to have

• Experience with a major cloud platform, MLOps practices, or AI services and startup environments.

Benefits and work setup

• Opportunity to help establish a new business area and contribute directly to customer AI projects.