AI Engineer

This is a remote position.

AI Developer/Engineer

Company: TeamFicient

Location: Remote

Employment Type: Full-Time

Work Schedule

Time Range: Between 7 AM and 7 PM CST

Working Hours: 9 hours per day (8 working hours + 1-hour break)

Days Off: TBD (2 days per week)

Why Join Us?

At Teamficient , our team spans multiple countries and regions, and we stay connected by operating within EST, CST, and PST time zones.

Work Without Borders: Collaborate daily with experts from around the world and gain international exposure.

Built for Remote: Join a fully remote culture designed for autonomy, flexibility, and trust.

Diverse Perspectives: Be part of a multicultural team where different backgrounds are our greatest strength.

Grow Globally: Expand your career on a global stage, learning how business works across different cultures and continents.

About the Role

TeamFicient is looking for an experienced AI Developer/Engineer to design, build, and scale production-grade AI applications that deliver real value to our clients. You'll work at the intersection of applied AI, backend engineering, and cloud infrastructure, building systems that are robust, reliable, and ready for the real world.

If you have a proven track record of shipping LLM and RAG-based systems in production, this role is for you.

Core Responsibilities

AI Application Development

Design and build AI-powered applications using LLMs, RAG architectures, and other applied AI systems

Develop and maintain backend services that support AI platforms and integrate seamlessly with cloud infrastructure

Build and maintain integrations across various applications to extend AI capabilities

Cloud and Infrastructure

Deploy, optimize, monitor, and troubleshoot AI solutions on AWS, Azure, and/or GCP

Implement containerization and orchestration strategies using Docker and Kubernetes

Ensure AI systems meet performance, scalability, and reliability standards in production

Architecture and Collaboration

Design scalable AI architectures that translate business requirements into technical solutions

Collaborate with cross-functional teams throughout the full development lifecycle

Contribute to code reviews, technical documentation, and engineering best practices

Candidate Qualifications

Must-Haves

5+ years of professional experience in AI engineering, machine learning, or software engineering with an AI focus, including production deployments and strong proficiency in Python and AI/ML frameworks, with a degree in Computer Science, Engineering, or equivalent practical experience

2-3 years of hands-on experience with LLMs and RAG architectures in production environments, including vector databases

3+ years of experience with cloud platforms, AWS, Azure, or GCP

2+ years of experience with Docker and Kubernetes for containerization and orchestration

Good to Haves

Familiarity with MLOps practices and tools for model deployment and monitoring

Knowledge of additional programming languages such as Go, Java, or JavaScript/TypeScript

Experience with CI/CD pipelines and infrastructure as code (Terraform, CloudFormation)

Contributions to open-source AI/ML projects or active participation in the AI community

Master's degree or PhD in Computer Science, Machine Learning, AI, or a related field

Originally posted on Himalayas