AI Cloud Operations Lead - Remote

Lensa; Austin (TX); Remote; USD 120,000 - 180,000; Full time

Job summary

A leading company is seeking an experienced AI/ML Engineer to design and maintain AI workflows in AWS environments. The role involves collaboration with various teams to create automated solutions, requiring extensive experience in AI/ML platforms and AWS services. Candidates should have strong communication skills and a relevant Bachelor's degree.

Qualifications

• 12+ years of industry experience with at least 2 years in a senior role.
• Expertise in AWS services and proficiency in Python, Java, or JavaScript.
• Strong communication skills and adaptability required.

Responsibilities

• Developing and managing AI/ML pipelines using AWS services.
• Designing and optimizing RAG pipelines with LangChain or HayStack.
• Implementing CI/CD pipelines and infrastructure-as-code practices.

Skills

AWS services

Python

Java

JavaScript

AI/ML platforms

Large-scale data processing

Communication skills

Adaptability

Education

Bachelor's degree in a relevant field

Tools

Pytorch

Jupyter

Cloudwatch

Prometheus

Grafana

Job description

SitusAMC is seeking a highly experienced professional to design, implement, and maintain AI and Machine Learning workflows primarily within AWS cloud environments. The role involves collaboration with AI developers, data engineers, and business teams to develop end-to-end automated, secure solutions leveraging AWS services and modern AI frameworks. Key responsibilities include:

1. Developing and managing AI/ML pipelines using AWS services such as Bedrock, Sagemaker, and Vector Databases.
2. Designing and optimizing RAG pipelines with LangChain, HayStack, or AutoGen.
3. Creating autonomous agent architectures and implementing prompt engineering techniques.
4. Exploring new LLM architectures to enhance RAG capabilities.
5. Integrating and fine-tuning NLP models within workflows.
6. Designing scalable, secure, and cost-efficient cloud infrastructure.
7. Implementing CI/CD pipelines and infrastructure-as-code practices.
8. Supporting data scientists with data exploration and hypothesis testing using Pytorch and Jupyter.
9. Collaborating with product teams to deliver AI solutions.
10. Monitoring system performance with tools like Cloudwatch, Prometheus, and Grafana.

Qualifications include a Bachelor’s degree in a relevant field, 12+ years of industry experience with at least 2 years in a senior role, expertise in AWS services, proficiency in Python, Java, or JavaScript, and experience with AI/ML platforms and large-scale data processing frameworks. Strong communication skills and adaptability are also required.