The opportunity

We're recruiting a Senior AI Engineer for the AI practice of a global advisory firm, based in Kyiv. The team designs and builds AI solutions and agentic applications for large enterprises, combining advanced software development with robust data engineering.

The role

You'll lead the design and development of AI solutions, working directly with client technical teams. You'll independently own major technical workstreams and help shape how agentic AI is built and deployed in client environments.

What you'll do

Build: architect and build scalable, modular and reproducible data pipelines for ML and AI applications, and develop software products and services that are maintainable, scalable and secure.
GenAI and agentic applications: develop, integrate and extend agentic AI platforms and use cases, making practical design decisions across application architecture, AI orchestration, data integration and deployment.
Client delivery: work with client technology teams to assess data landscapes, ensure data quality and support the deployment of AI use cases into client environments.
Advisory: take part in cross-functional problem-solving sessions with client leaders, advising on solution design and implementation choices.
Capability building: mentor client teams on engineering best practices, user-centric design and Agile values, and contribute to reusable internal assets and R&D.

What you bring

Degree in Computer Science, Engineering, Mathematics or equivalent experience
5+ years of professional experience building and deploying data solutions and software products
Strong coding skills in Python, with Scala or Java a plus
Experience with structured, semi-structured and unstructured data on distributed frameworks (e.g. Spark, Dask), cloud platforms (AWS, Azure, GCP) and analytics libraries
Hands-on Docker and Kubernetes experience, plus DevOps, DataOps or MLOps practice with tools such as PySpark, Airflow, Databricks or Kedro
Hands-on experience building or integrating GenAI applications, including LLMs, retrieval-augmented generation (RAG), tool calling and workflow orchestration
A good understanding of end-to-end AI application architecture: APIs, system integration, model selection, security, observability and production deployment
Exposure to ML frameworks (TensorFlow, PyTorch, Keras, Scikit-Learn) and familiarity with AI governance, safety and responsible AI
Experience working in Agile teams, including sprint ceremonies
Strong time management in autonomous environments
Business-level fluency in English and the local language, with the ability to engage stakeholders at all seniority levels

Logistics

Location: Kyiv
Competitive salary based on location, experience and skills, plus a comprehensive benefits package
Global team with colleagues across 65+ countries
Structured apprenticeship, coaching and development programmes