Job Description

About Nortal:

We’re Nortal. We think big and create cutting-edge digital solutions with a global reach. And with 25 years of experience, 2,700+ professional experts, and half a billion people worldwide impacted by our work, we believe we’ve got the numbers to back up that statement. 

Our global teams have played a significant role in many Fortune 500 companies’ projects and systems and have been the driving force of digital transformation for governments, healthcare institutions, and leading enterprises worldwide. We combine best-in-class strategic consulting with software engineering, data, and design practices to bring our visions to life.

The client you’ll work with:

You will join an extension team of our client – iBusiness.

iBusiness is a leading technology company transforming the way financial institutions, small businesses, and enterprises work. As a pioneer in secure AI, automation, and AI software development, we build infrastructure and platforms that empower teams to modernize processes and work more efficiently without sacrificing compliance or security. Our workflow, verticalized, and point solutions enable seamless digital transformation, giving organizations of all sizes the tools they need to compete, innovate, and grow.

Join us and be part of a team that’s building solutions designed to help businesses thrive!

The role:

We are seeking an experienced expert AI Knowledge Data Engineer to design, implement, and scale state-of-the-art AI systems that combine large language models (LLMs), advanced retrieval techniques, cognitive memory architectures, including knowledge representation, and data fusion.

In this role, you will orchestrate robust data pipelines, architect scalable training data solutions, and build the foundational knowledge bases that power next-generation AI agents. You will collaborate with cross-functional teams to ensure our systems efficiently retrieve, contextualize, and generate accurate information for diverse business applications.

Responsibilities

What you'll do:

• Architect, implement, and optimize retrieval-augmented generation (RAG) workflows by integrating local LLMs (e.g., Llama) with retrieval mechanisms (vector search, Elasticsearch, FAISS, Weaviate)
• Design, build, and maintain scalable data pipelines for ingesting, transforming, indexing, and retrieving structured and unstructured data from diverse sources
• Design, build, and scale addressable services and tools specifications that can be leveraged by LLMs and Аgents to orchestrate workflows
• Orchestrate and scale training data operations, including data curation, versioning, and lineage tracking for large-scale LLM training and fine-tuning
• Develop and maintain ontologies, knowledge graphs, and semantic data models to structure and integrate domain-specific knowledge for improved retrieval and reasoning
• Implement and optimize knowledge retrieval strategies (dense/sparse retrieval, ranking algorithms) to maximize system accuracy and relevance
• Aggregate disparate knowledge bases and heterogeneous data into a fused approach for access to relevant contextual information
• Design cognitive memory systems for AI agents, enabling persistent knowledge retention and contextual awareness across interactions
• Collaborate with AI researchers, data scientists, and engineers to align knowledge architecture with business objectives and ensure data quality
• Evaluate and integrate new technologies and research advancements in LLMs, RAG, information retrieval, and knowledge representation
• Maintain clear and comprehensive documentation of models, pipelines, and workflows

Qualifications

What we're looking for:

• Bachelor’s or Master’s degree in Computer Science, Data Science, Machine Learning, or a related field
• Proven experience designing and scaling data pipelines and training data workflows for LLMs or similar AI systems
• Strong background in information retrieval systems, vector search technologies, and RAG frameworks (e.g.,FAISS, Pinecone, Elasticsearch, Milvus)
• Proficiency in programming (Python) and machine learning libraries (TensorFlow, PyTorch )
• Experience with ontologies, knowledge graphs, and semantic technologies (RDF, OWL, SPARQL)
• Familiarity with distributed data processing and orchestration tools (e.g., Spark, Airflow, Kubeflow)
• Excellent analytical, problem-solving, and communication skills
• Ability to work collaboratively in a cross-functional, fast-paced environment

Brownie points:

• Experience with LLM fine-tuning, prompt engineering and RAG optimization
• Familiarity with data-centric AI principles and training data quality assessment
• Experience with cloud platforms and scalable storage solutions
• Background in cognitive memory architecture or AI agent design

Why work with us:

• Great work-life balance
• Competitive remuneration package
• Exceptional social package & special discounts
• Supplemental health & dental care
• Team bonding events
• Excellent office location & facilities
• Relaxing & gaming areas
• Free bike parking & showers

How to apply:

If you recognize yourself in this role, please send your CV in English.

Our team would be excited to get in touch if your skillset and experience match the profile we look for.

Of course, all applications will be treated as strictly confidential.

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