Technical Lead – AI Engineering

This is a remote position.

Job Title: Technical Lead – AI Engineering

Our client is a fast-growing technology company specializing in AI innovation and intelligent automation. We design and deploy cutting-edge AI solutions that combine human creativity with artificial intelligence to drive measurable business impact. With a distributed remote team across multiple time zones, the company fosters a collaborative, hands-on environment that values curiosity, ownership, and technical excellence.

Why Are They Hiring for This Role?
As the company scales its AI-driven initiatives, it is seeking an experienced Technical Lead, AI Engineering to guide a team of AI and Machine Learning engineers in developing scalable, high-performance AI systems. This is a hands-on leadership position for someone who excels at both strategic technical direction and direct code contribution — shaping architecture, mentoring engineers, and delivering advanced AI infrastructure in a dynamic, fast-paced environment.

Team
You’ll lead a distributed team of 3–7 engineers, acting as both mentor and technical contributor. Working closely with product managers, data scientists, and DevOps engineers, you’ll ensure the delivery of scalable, secure, and efficient AI systems. The team operates in a fully remote setup that values autonomy, technical rigor, and continuous learning.

Responsibilities:

1. Own architecture decisions and define the technical roadmap for AI systems that scale with organizational needs.
   

2. Provide technical leadership and mentorship, promoting best practices in coding, architecture, and system design.
   

3. Oversee the design and implementation of machine learning infrastructure — from data pipelines to model deployment, ensuring reliability and performance.
   

4. Implement and uphold high engineering standards, including testing, CI/CD, and code review processes.
   

5. Lead project planning and execution, managing priorities, timelines, and deliverables in a remote environment.
   

6. Collaborate cross-functionally with product, data, and DevOps teams to align AI initiatives with business goals.
   

7. Evaluate and integrate new AI/ML frameworks, tools, and technologies to drive innovation and optimize performance.
   

8. Monitor system health and model performance, proactively addressing scalability, accuracy, and reliability.
   

9. Foster a culture of continuous improvement, career growth, and knowledge sharing within the team.
   

Requirements

1. 5+ years of professional experience in software engineering, including 2+ years in a technical lead or similar leadership role.
   

2. Hands-on experience in AI/ML infrastructure, such as model training, deployment, or MLOps pipelines.
   

3. Strong programming skills in Python and familiarity with TypeScript.
   

4. Experience designing and implementing scalable, distributed systems and data pipelines.
   

5. Solid understanding of modern ML frameworks (e.g., TensorFlow, PyTorch, scikit-learn) and cloud platforms (AWS,
   GCP, or Azure).
   

6. Familiarity with Docker, Kubernetes, and CI/CD best practices.
   

7. Excellent leadership, communication, and collaboration skills, particularly in remote/distributed teams.
   

8. Strong problem-solving mindset, capable of debugging complex systems and ensuring code quality.
   

9. Bachelor’s degree in Computer Science, Engineering, or related field (or equivalent practical experience).
   

Preferred Qualifications

1. Master’s or Ph.D. in Machine Learning, Data Science, or
   related discipline.
   

2. Experience with Large Language Models (LLMs), NLP,
   computer vision, or generative AI.
   

3. Prior contributions to open-source AI/ML projects, research
   publications, or patents.
   

4. Background in startups or high-growth environments with
   strong engineering cultures.
   

5. Familiarity with MLOps, AI observability, or real-time data
   processing.
   

Timezone
Flexible across U.S. time zones, with some overlapping hours in particular
for the Hawaiian time zone for collaboration.

Duration
Long Term