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Nokia

AI Expert

Nokia is hiring an AI Expert. Level rates it ; you can apply on Nokia.

Level's read on this job

  • On Level's scale, this role is Works on AI ●●●○: the daily work is on AI products, without building the model.
  • The posting mentions Semantic Kernel, RAG and AI evaluation among its tools and skills.
  • Nokia has 576 other open roles on Level.
  • Posted within the past two weeks.

AI in this role

semantic-kernel
ragai-evaluation

We are looking for an experienced Senior AI Software Engineer to join our team and contribute to the development of Artificial Intelligence solutions supporting our engineering and R&D activities.

The position combines software engineering and Generative AI. You will design and develop applications leveraging Large Language Models (LLMs), enterprise data and modern AI platforms, while ensuring that these solutions can be effectively integrated into our existing software environment.

You will work closely with software engineers, architects, technical experts and project stakeholders to identify relevant AI use cases and transform them into practical, reliable and maintainable solutions.

As an experienced member of the team, you will be expected to work with a high degree of autonomy, contribute to technical and architectural decisions, and share your knowledge with other engineers working on AI initiatives.

Design and Develop AI Solutions

  • Design and develop applications and services leveraging Large Language Models (LLMs) and Generative AI.
  • Build AI-powered solutions supporting engineering and R&D activities.
  • Develop solutions using Microsoft Azure AI services and Azure AI Foundry, as well as other approved AI technologies when appropriate.
  • Design and implement Retrieval-Augmented Generation (RAG) solutions combining LLMs with internal documents, knowledge bases and enterprise data.
  • Integrate AI models through APIs and SDKs into new or existing applications.
  • Design AI workflows involving multiple processing steps, models, tools or data sources.
  • Explore multimodal use cases involving text, documents and images when relevant.

     

Develop Enterprise Software

  • Design and develop backend applications, services and REST APIs.
  • Contribute to applications primarily based on C# and .NET / ASP.NET Core within the existing enterprise software environment.
  • Use Python when appropriate for AI development, experimentation, data processing or integration with the broader AI ecosystem.
  • Integrate applications with databases, enterprise systems and external APIs.
  • Write maintainable, reliable and well-documented code.
  • Diagnose and resolve technical issues across AI and application components.
  • Contribute to the technical architecture of new AI solutions.

     

Evaluate and Improve AI Solutions

  • Evaluate different AI models and approaches according to the requirements of each use case.
  • Design and improve prompts, system instructions and context-management strategies.
  • Understand and manage concepts such as tokens, context windows, embeddings and vector search.
  • Evaluate AI outputs in terms of quality, reliability and consistency.
  • Consider performance, latency and cost when designing AI solutions.
  • Identify limitations and risks associated with LLM-based solutions and propose appropriate technical approaches.
  • Contribute to the continuous improvement of existing AI applications based on usage and feedback.

     

Explore and Recommend Technologies

  • Follow developments in Generative AI, LLMs and related technologies.
  • Experiment with new models, frameworks and approaches when they could bring value to the organization.
  • Compare technical alternatives and contribute to technology and architecture choices.
  • Help determine when Generative AI is appropriate for a use case and when a traditional software approach may be more suitable.

     

Collaborate and Share Knowledge

  • Work with engineers and domain experts to understand their needs and identify valuable AI use cases.
  • Translate functional needs into appropriate technical solutions.
  • Explain technical concepts and architectural choices to both technical and non-technical stakeholders.
  • Produce and maintain technical documentation for developed solutions.
  • Share knowledge and good practices with other developers.
  • Provide technical guidance to junior engineers or students contributing to AI projects.
     

Required Skills & Qualifications

  • Bachelor's or Master's degree in Computer Science, Software Engineering, Artificial Intelligence or a related technical field, or equivalent professional experience.
  • Significant professional experience in software development.
  • Strong backend development and software engineering skills.
  • Professional experience with C#/.NET and/or Python, with the ability and willingness to work with both technologies when required.
  • Hands-on experience developing applications or services using Generative AI and Large Language Models.
  • Good understanding of LLM concepts such as prompting, context management, tokens and model limitations.
  • Experience integrating services and systems through REST APIs.
  • Experience working with relational databases and data-driven applications.
  • Good understanding of software architecture and application integration.
  • Ability to investigate complex technical problems and propose pragmatic solutions.
  • Ability to work autonomously and take ownership of technical topics.
  • Good communication and collaboration skills in an international environment.
  • Professional working proficiency in English.

 

Nice to have

The following skills are valuable but are not mandatory:

  • Experience with Microsoft Azure AI Foundry or similar enterprise AI platforms.
  • Experience with Retrieval-Augmented Generation (RAG) architectures.
  • Knowledge of embeddings, vector databases and semantic search.
  • Experience with AI orchestration frameworks such as Microsoft Semantic Kernel or equivalent technologies.
  • Experience working with both C#/.NET and Python in professional projects.
  • Experience with ASP.NET Core and enterprise web applications.
  • Experience integrating AI solutions with enterprise data sources or business systems.
  • Experience with AI evaluation, observability or usage and cost monitoring.
  • Knowledge of locally deployed or open-source LLMs.
  • Experience with multimodal AI, document processing, Vision models or OCR.
  • Experience using AI-assisted development tools.

     

What we are looking for

We are looking for an experienced engineer who combines strong software development skills with practical Generative AI experience.

The ideal candidate should be able not only to experiment with an LLM, but also to transform an AI concept into a maintainable application that can interact with existing systems and enterprise data.

We value technical curiosity and pragmatism. The AI ecosystem evolves quickly, so the ability to evaluate new technologies, understand their strengths and limitations, and select the right approach for a given problem is more important than expertise in any single framework.

We are also looking for someone who can bring experience to the team: an engineer capable of working independently, contributing to technical decisions and helping less experienced team members develop their AI engineering skills.

How we rate this

AI Expert at Nokia rates 69 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.

Classification

Works on AI. The daily work is on AI products, without building the model.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

RAGAI EvaluationSemantic Kernel

Questions you could be asked

  1. How would you design a retrieval step so the model answers from real data instead of guessing?
  2. How do you decide that one model's output is better than another's for a given task?
  3. What are the limits of Semantic Kernel that you've run into, and how did you work around them?
  4. Describe a typical day in a role like this one: which parts run through AI directly?
  5. If you removed AI from this role, what would be left, and how do you decide what still needs a human?

Adapt your resume

  • List these exact terms on your resume: RAG, AI Evaluation, and Semantic Kernel. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
  • Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.

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