Senior AI Engineer (Customer Facing)

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

Job summary

RapidCanvas is seeking a senior AI/ML engineer to deliver production AI applications for enterprise customers. You will connect business needs with applied ML, designing agent and language model solutions, implementing them, and continuously optimizing results.

You will collaborate with customer data science teams and internal engineering, product, and solutions teams to ensure scalable, reliable deployments and maintainable Python code that meets performance and scale goals.

Qualifications

• 5+ years AI/ML or backend engineering experience.
• Proficient in Python and building scalable APIs.
• Strong ML/deep learning grounding and practical LLM use.
• Hands-on with LangChain, LangGraph or CrewAI and vector DBs.
• Excellent communication and ability to manage multiple projects.

Responsibilities

• Clarify customer goals and translate them into reliable AI solutions.
• Build multi-step agents for customer use cases across data sources.
• Create retrieval-augmented generation pipelines for grounding models.
• Oversee data prep, model development, deployment, and monitoring.
• Collaborate with data science, engineering, and product teams for integrations.
• Provide product feedback and maintain scalable Python code.

Skills

Python

AI/ML engineering

Backend services

APIs

Language models

Generative AI

Agent frameworks

LangChain

LangGraph

CrewAI

Vector databases

Tools

Pinecone

Weaviate

FAISS

Job description

Role overview Deliver production AI applications for enterprise customers as a senior technical partner who can connect business needs with applied machine learning. The work spans customer discovery, agent and language model solution design, implementation, and ongoing optimization, with regular collaboration across customer and internal teams.

Responsibilities

• Clarify customer goals and turn them into reliable, scalable AI solutions while guiding projects to the intended outcomes.
• Build and integrate multi-step agents for customer use cases, including automation that draws on logs, APIs, and other infrastructure signals.
• Create retrieval-augmented generation pipelines to ground language models in customer-specific information.
• Oversee the solution lifecycle, including data preprocessing, model development, deployment, monitoring, and optimization.
• Partner with customer data science teams and internal solutions, engineering, and product groups to support integrations and customer-built applications.
• Provide product feedback and write maintainable Python that supports performance, accuracy, and scale.

Requirements

• At least five years of hands-on AI/ML engineering or backend systems experience, with recent experience involving language models or intelligent agents.
• Proficiency in Python and demonstrated experience building scalable backend services or APIs.
• Strong grounding in machine learning, deep learning, and generative AI, including hands-on use of language model platforms.
• Practical experience with agent frameworks such as LangChain, LangGraph, or CrewAI and vector databases such as Pinecone, Weaviate, or FAISS.
• Strong customer communication and presentation skills, with the ability to work independently and manage several projects.

Nice to have

• Experience with cloud platforms, MLOps, AI services, or startup environments.

Benefits and work setup

• High-impact opportunity to contribute to a new business area and deliver AI solutions directly with enterprise customers.