SW Tech lead for GenAI/AI

SW Tech lead for GenAI/AI

A Snapshot of Your Day

The role of SW AI technology expert is essential to building and strengthening partnerships with key AI software suppliers and technology providers. You will play a pivotal role in aligning partner capabilities with internal business and technical needs, helping to scale AI SW coding innovation solutions, drive digital transformation, and accelerate go-to-market strategies. Your day will involve translating strategic goals into actionable technical collaborations, fostering stakeholder trust, and supporting the integration of advanced software technologies into our product and platform ecosystems.

In this role, you will report directly to the SW digitalization and technology lead, working closely with SW developers, IT and cloud architects, and external partners to evaluate, test and implement joint initiatives. You will also collaborate with the leadership team and be involved in the strategic roadmap.

Your key responsibilities will include:

· Identify, evaluate, test and engage strategic AI SW partners aligned with business and technology goals.

· Serve as the technical point of contact for partner collaboration, supporting joint solution development and POCs.

· Translate complex business requirements into integrated technical solutions in partnership with internal stakeholders.

· Drive performance metrics with vendors, ensuring timely delivery, compliance, and value creation.

· Lead co-development initiatives involving cloud platforms (AWS, Azure, GCP) and emerging technologies.

· Facilitate knowledge exchange between internal engineering teams and partner developers.

· Define engagement models, processes, and documentation to scale partnership success across regions and teams.

· Collaborate with Agile product teams to embed partner capabilities into DevOps workflows and software delivery pipelines.

How You’ll Make an Impact

· Build a resilient AI SW partner ecosystem that enhances technical capabilities, accelerates time-to-market, and increases innovation throughput.

· Ensure technical alignment between external partners and internal development teams to streamline solution integration.

· Strengthen product roadmaps by enabling access to AI cutting-edge SW technologies through strategic partnerships.

· Increase efficiency by implementing AI solution into the SW development space.

· Reduce operational risks by vetting partner solutions for SW security, scalability, and long-term support.

What You Bring

Education:
Master’s degree in Computer Science or Information Systems or equivalent
Technical Requirements:
5+ years of experience in software development, preferably with a focus on partner.
Proven experience with AI development systems.
Proven experience in cloud platforms (AWS, Azure, GCP).
ecosystem integration.
Hands-on experience with emerging technologies and AI tools.
Proficiency in programming languages such as Python, Java, Node.js.
Solid understanding of software development, architecture, POCs, Agile methodologies, and DevOps practices.
General Requirements:
Strong ability to translate business needs into scalable technical solutions.
Proven experience in stakeholder engagement, vendor management, and partnership negotiation.
Excellent verbal and written communication skills across technical and non-technical audiences.
A natural networker with the ability to build and maintain strategic external relationships.

About the Team

The Digital Products & Solutions organization is responsible for developing software solutions for both internal and external customers. These solutions include Edge Computing and applications, On-site sensor technology integration, Cloud-based platforms and cloud-based software solutions and applications.

The solutions, applications, and platforms we provide allow data acquired to be used to improve the operation and maintenance of power plants and industrial facilities of all sizes this includes the development of digital twins, analytics platforms and agents, artificial intelligent and machine learning applications and algorithms.