Lead AI Engineer Digital Service Solutions

Hitachi Energy Kraków 2026-10-07

Your Background

University degree (Bachelor’s or Master’s) in Computer Science, Data Science, Engineering, or a related technical field
Proven experience in designing, implementing, or governing applied AI/ML solutions in industrial, IoT, or service‑oriented environments
Strong understanding of end‑to‑end AI pipelines, including data preparation, model development, deployment, and monitoring
Experience integrating AI into enterprise‑scale digital solutions using cloud platforms, microservices, and MLOps practices
Ability to translate AI techniques into interpretable, operationally relevant outcomes aligned with service and domain needs
Experience working in cross‑functional environments across R&D, engineering, service, and digital organizations
Strong communication skills and ability to influence architecture and solution decisions across stakeholders
Experience with LLM‑based systems, agentic AI, or advanced analytics platforms is an advantage
Familiarity with AI governance, ethics, compliance, and regulated industrial environments is meriting

The Opportunity

Business Unit Service is at the forefront of delivering advanced digital and outcome‑based service solutions worldwide. Our Service R&D organization develops next‑generation digital service solutions that leverage IoT, cloud platforms, data, and AI to enable long‑term asset performance, reliability, and operational excellence across the energy and industrial domain.

As Lead AI Engineer, you will play a key role in defining and evolving AI capabilities across digital service solutions. You will ensure that AI models, agentic workflows, and AI‑enabled services are architected, governed, and integrated as scalable, reusable, and enterprise‑ready components embedded into end‑to‑end service operations.

This role directly impacts the success of intelligent service operations, predictive and prescriptive analytics, and AI‑augmented decision‑making, where model quality, robustness, explainability, and lifecycle governance are critical for business value and customer trust.

Our benefits offering for this role generally includes:

•Private medical care and life insurance

•Access to fitness and wellness programs

•Access to benefits platform with discounts and perks

•Employee Capital Plans (PPK)

•Equipment for working from home or allowances for setting up a workplace at home

•Spectacles and contact lenses allowance

•Company events and team‑building activities

•Psychological support program

•Free parking available

,[Defining and owning the AI R&D capability strategy and architecture for digital service solutions, covering applied machine learning, advanced analytics, and LLM‑based and agentic AI systems , Establishing architectural principles and standards aligned with cloud‑native delivery models, industrial scalability, and long‑lifecycle service solutions , Translating service and domain needs into AI models, use cases, and solution‑level designs embedded in end‑to‑end workflows and decision processes , Designing and governing AI model lifecycles, including problem framing, validation, deployment, monitoring, and controlled evolution , Ensuring AI outputs are actionable, interpretable, and aligned with operational realities and business objectives , Leading the design and governance of agentic AI workflows that combine reasoning, orchestration, and automation across service operations , Collaborating with data platform, digital platform, and IT teams to ensure AI solutions are supported by scalable data pipelines, feature management, and analytics services , Establishing principles and controls for AI quality, explainability, bias mitigation, and ethical use aligned with regulatory and industrial requirements , Contributing to AI portfolio alignment, reuse, and standardization across solutions to reduce fragmentation and accelerate value realization , Acting as a technical authority and trusted advisor, guiding architecture decisions and supporting capability development across Service R&D ] Requirements: AI, ML, IoT, Cloud platform, Microservices, MLOps, Communication skills Additionally: Private healthcare, Company Events, Life insurance, Discounts, Free parking.