Senior AI Team Lead & Systems Architect

CODEX

Sarıyer

On-site

TRY 400,000 - 700,000

Full time

14 days+

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Job summary

CODEX invites a senior AI Team Lead to manage and mentor an AI/Data Science team. You will translate business objectives into technical roadmaps, drive architectural decisions, and ensure scalable data pipelines and reliable model deployment.

You will stay ahead of AI trends and guide PoCs to production, while leading multi-disciplinary collaboration with PMs and engineering leads. The role requires 7+ years in AI/Data Science, strong Python expertise, experience with RAG/LLM frameworks, and

Qualifications

BSc degree in Computer Engineering, AI, Mathematics, or a related field (MSc/PhD preferred).
Minimum of 7 years of professional experience in Data Science, MLOps, and AI development after bachelor graduation.
Currently holding a senior or lead-level position.
Strong proficiency in Python programming and data science libraries.
Experience with recommendation systems algorithms and concepts.
Hands-on experience with frameworks for building and integrating RAG and LLM-based applications.
Proficiency with CI/CD processes and MLOps best practices.
Proficiency in written and spoken English.
Ability and motivation to self-teach, enter new domains, and manage ambiguity.

Responsibilities

Lead, mentor, and conduct performance reviews for an AI team.
Oversee the team's workflow (Agile/Scrum), ensuring efficient delivery, high code quality, and robust CI/CD/MLOps practices.
Manage project planning, resource allocation, and timeline estimation for AI initiatives.
Translate high-level business objectives into technical roadmaps for AI and Data Science products.
Drive high-level architectural decisions, selecting the right tools, frameworks, and cloud infrastructure to ensure scalability and performance.
Stay ahead of the curve on AI trends and guide the team in moving valid PoCs into production.
Provide expert guidance on complex problems and mentor team members on technical challenges.
Ensure the reliability and scalability of data pipelines, labeling processes, and model deployment strategies.
Collaborate with Product Managers and other Engineering Leads to ensure cross-functional alignment.