Senior AI & Data Architect — Forward Deployed

Kyndryl; Milano; Hybrid; EUR 90,000 - 130,000; Full time

Job summary

Kyndryl is seeking a Senior Forward Deployed Engineer in Italy to design and implement cloud-native AI and data architectures, merging AI-driven solutions with enterprise workflows. You will lead architecture projects, collaborate with global teams, and drive scalable AI initiatives across the organization.

This role emphasizes governance, model lifecycle management, and real-time data processing, offering a hybrid work arrangement and opportunities for continuous learning in AI and data

Qualifications

• Proven experience designing cloud-native AI and data architectures.
• Strong expertise in generative AI, agentic AI, LLMs and orchestration frameworks.
• In-depth knowledge of MLOps, AI governance, and model deployment at scale.
• Understanding of data platforms including data lakes and real-time streaming.
• Ability to integrate AI services with enterprise applications.

Responsibilities

• Define and implement modern data architectures leveraging cloud-native technologies, data lakes, and real-time streaming platforms.
• Design AI-driven solutions including generative and agentic AI frameworks integrated with enterprise workflows.
• Establish best practices for MLOps, AI governance, and model lifecycle management to ensure reliability and compliance.
• Collaborate with cross-functional teams to deliver large-scale AI and data initiatives.
• Evaluate emerging technologies to keep the company at the forefront of AI and data transformation.

Skills

Cloud-native AI

Generative AI

Agentic AI

LLMs

MLOps

AI governance

Data lakes

Real-time streaming

Enterprise integration

Cloud architectures

Tools

AI orchestration tools

Vector databases

Semantic search

RAG

Job description

Kyndryl is seeking a Senior Forward Deployed Engineer in Italy to design and implement cloud-native AI and data architectures, merging AI-driven solutions with enterprise workflows. You will lead architecture projects, collaborate with global teams, and drive scalable AI initiatives across the organization.

This role emphasizes governance, model lifecycle management, and real-time data processing, offering a hybrid work arrangement and opportunities for continuous learning in AI and data