Lead AI Platform Engineer

i2d consulting; Warszawa; On-site; PLN 180,000 - 260,000; Full time

Job summary

i2d consulting is seeking a Senior AI Platform Engineer to design, develop, and operationalize AI and platform automation solutions on the ADAP platform, accelerating developer experience and data product insights at enterprise scale.

You will collaborate with data engineers, architects, product owners, and domain experts to translate complex business challenges into robust AI solutions and scalable deployments across the organization.

Qualifications

• 10+ years in data/software/platform engineering in large-scale environments.
• Proven production-grade AI systems experience preferred.
• Experience with LLMs, NLP, MCP servers, agentic workflow deployment, and AI platform architectures.
• Hands-on with Databricks, Spark, Delta Lake, and lakehouse paradigms.
• Expertise integrating AI solutions with large-scale data platforms.
• Strong CI/CD, automation, monitoring, and model observability.

Responsibilities

• Design end-to-end AI solutions on the ADAP platform, including ingestion, training, deployment, and monitoring.
• Build reusable AI components and pipelines to accelerate deployment.
• Follow software engineering practices for modularity and maintainability.
• Collaborate with data engineers, platform teams, and stakeholders to translate needs into designs.
• Mentor junior engineers and support capability-building.

Skills

Data engineering

Platform engineering

Software engineering

Python

SQL

Cloud-native development

Tools

Databricks

Apache Spark

Delta Lake

Kubernetes

CI/CD tooling

Job description

Location of Requirement Poland Contract and Onsite role

Role Overview

As a Senior AI Platform Engineer within Client’s Data Analytics Platform (ADAP) organization, you will design, develop, and operationalize AI and platform automation solutions that accelerate developer experience and data product insights across the company. You will combine deep technical expertise in AI engineering, data systems, and software architecture to build scalable, secure, and high-performance AI capabilities on the ADAP platform.

In this role, you will closely collaborate with data engineers, architects, product owners, and domain experts to translate complex business challenges into robust AI solutions that can be deployed at enterprise scale.

Key Responsibilities

AI Solution Design & Development

• Architect and implement end-to-end AI solutions—data ingestion and preparation, AI engineering, model deployment, and monitoring.
• Build reusable AI components, frameworks, and pipelines that accelerate model usage and deployment across teams.
• Ensure solutions follow software engineering best practices, including modularity, testability, and maintainability.
• Integrate AI capabilities into Client’s ADAP platform, enabling scalable training, model tracking, and lifecycle management.
• Optimize AI workloads on Data bricks, Spark, and Azure-based data platforms.
• Implement cloud-native and micro services-based AI deployment architectures.
• Leverage automation and infrastructure-as-code to ensure reproducibility and operational excellence.

Technology Leadership& Innovation

• Drive the adoption of cutting-edge AI techniques, tooling,and frameworks.
• Partner with peer architects to align AI design with data platform strategy.
• Explore and integrate emerging technologies (e.g., LLMs,generative AI, streaming ML, vector databases).

Collaboration & Stakeholder Engagement

• Work cross-functionally with data engineers, platform teams, analytic steams, and business stakeholders.
• Translate analytical needs into clear technical requirements and solution designs.
• Mentor junior engineers and support capability-building across the organization

Required Skills & Qualifications Experience

• 10+ years in data/software engineering, platform engineering, or software engineering within large-scale environments.
• Proven experience delivering production-grade AI systems would be a preference. Technical Expertise
• Experience with LLMs, NLP, MCP servers ,agentic workflow deployment and AI platform architectures.
• Hands-on with Data bricks, Spark, Delta Lake, and lake house paradigms.
• Expertise integrating AI solutions with large-scale data platforms.
• Strong experience with CI/CD, automation, monitoring, and model observability.
• Familiarity with micro services, containers, and Kubernetes.
• Software Engineering:
• Proficiency in Python,SQL, and cloud-native development patterns.
• Ability to design secure, scalable, and high-performance AI components.

Soft Skills

• Strong communication and stakeholder management skills.
• Ability to lead technical direction and influence cross-functional teams.
• Problem-solving mind set with a focus on delivering value.