Lead AI Platform Engineer | LLM | AI Platform | Databricks

Accountabilities: The role is responsible for leading the technical direction of AI platform capabilities, ensuring scalable, secure, and reusable solutions that accelerate the adoption of artificial intelligence across the organization.

Lead the evolution of enterprise AI platforms and shared AI capabilities.

Define governance standards for the use of LLMs, AI Gateway, Skills, MCPs, and intelligent agents.

Design reusable architectures, frameworks, and components to accelerate AI initiatives.

Evaluate emerging technologies and contribute to the strategic roadmap for AI platform evolution.

Establish MLOps standards, including MLflow practices, version control, and governance processes.

Act as a technical reference for Analytics Engineers and teams consuming AI platform capabilities.

Collaborate with Cybersecurity, Architecture, and Platform Engineering teams to ensure secure and compliant solutions.

Mentor engineers and promote best practices in AI Platform Engineering.

Requirements:

The ideal candidate has strong experience building AI platforms and enterprise-grade solutions, combining technical depth with the ability to influence architecture decisions and guide teams.

Solid experience with AI platforms and Large Language Models (LLMs).

Proven experience building shared AI frameworks, libraries, or platforms.

Strong Python development skills for AI solution engineering.

Experience with AI Gateway, MLflow, MLOps, and Databricks AI.

Knowledge of AI governance, security practices, and enterprise AI standards.

Ability to define technical patterns and influence architectural decisions.

English proficiency for collaboration in a global environment.

Experience with LangChain, LangGraph, or intelligent agent frameworks is a strong advantage.

Experience with Model Context Protocol (MCP) and AI Agents for enterprise environments is a plus.

Knowledge of Unity Catalog, Data Governance, and cloud platforms such as Microsoft Azure is desirable.

Certifications related to Microsoft Azure or Databricks are considered a differentiator.

Benefits:

The company offers a work environment focused on innovation, professional growth, and employee well-being, with benefits including:

Profit-sharing and performance-based programs.

Health and dental insurance.

Flexible benefits card.

TotalPass access.

Access to wellness and mental health support programs.

Language learning program.

Partnership with educational institutions for professional development.

Hybrid work model and flexible working hours.

Internal training programs and structured career development plans.

Mentorship opportunities.

Extended parental leave.

Childcare assistance.

Continuous learning initiatives, including live coding sessions, coding dojos, discussion groups, and wellness activities.

How Jobgether works: We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team. We appreciate your interest and wish you the best!  Why Apply Through Jobgether? 

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