TL;DR

AI Technical Lead: Leading AI initiatives from the initial workshop phase up to technical implementation, acting as the primary technical consultant and architect for key international clients with an accent on defining AI success criteria and designing system architectures. Focus on solving tricky R&D challenges, defining custom AI/ML solutions, and architecting scalable AI solutions using Cloud-native services and open-source frameworks.

Company

%hirify_global% is a company working with the latest technologies for industry leaders.

What you will do

Lead technical workshops with clients to define AI success criteria, design system architectures, and determine implementation strategies.
Act as the hands-on technical lead for Cloud and AI projects, overseeing the lifecycle from concept to deployment.
Collaborate with sales and product teams to ensure AI proposals are technologically sound and deliver genuine business value.
Solve tricky R&D challenges, acting as the main consultant for defining custom AI/ML solutions.
Architect scalable AI solutions using Cloud-native services (e.g., Vertex AI, SageMaker) and open-source frameworks.
Lead engineers and interns, fostering their growth in AI and Cloud technologies.

Requirements

Extensive experience in AI/ML Engineering and Cloud Architecture roles.
Proven ability to run client-facing workshops and translate business goals into technical AI roadmaps.
Strong communication skills.
Experience in leading presales – defining technical aspects and scope of an AI project.
Deep hands-on experience with Cloud platforms (AWS, GCP, or Azure) and their specific AI/ML suites.
Strong background in R&D, GenAI/LLMs, and figuring out solutions in “greenfield” projects.
Proficiency in Python and ML frameworks (e.g., PyTorch, TensorFlow, LangChain).
Experience mentoring technical teams and driving best practices in code and architecture.

Nice to have

Cloud Certifications (e.g., AWS Certified Machine Learning – Specialty, Google Professional Machine Learning Engineer).
Experience with MLOps practices, CI/CD for ML, and containerization (Docker/Kubernetes).
Knowledge of AI governance, ethics, and security best practices.
Background in pre-sales engineering or technical consulting.

Culture & Benefits

Flexible employment and remote work.
Work with the latest technologies for industry leaders.
International projects with leading global clients.
Work comfortably in a relaxed and inspiring atmosphere that does not enforce a dress code.
Develop your skills at work – language classes come to you.
Take part in activities that support your physical and mental health.