AI Solutions Engineer
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Summary
Builds AI and machine-learning solutions for client engagements with McKinsey's QuantumBlack in Budapest — developing scalable data pipelines, secure data environments, and production-grade software while mentoring client teams. Core stack: Python, SQL, Spark/Dask, Airflow, Docker, Kubernetes, and AWS/Azure/GCP.
- Design and build innovative AI solutions combining advanced software development and data engineering
- Collaborate with global technologists, data scientists, and industry experts to transform businesses through advanced analytics and AI-driven solutions
- Develop scalable data pipelines tailored for machine learning and AI applications
- Build maintainable, scalable, and secure software products and services from the ground up
- Assess data landscapes, ensure data quality, and prepare data for advanced analytics models
- Manage secure data environments
- Contribute to research and development initiatives and internal asset development
- Participate in cross-functional problem-solving sessions with client leaders to shape digital strategies
- Mentor client teams on engineering best practices, user-centric design, and Agile values
- Partner with QuantumBlack, AI by McKinsey and QuantumBlack Labs teams to create cutting-edge machine learning systems
- Degree in Computer Science, Engineering, Mathematics, or equivalent experience
- 2+ years of professional experience in building and deploying data solutions and software products
- Strong coding skills in Python
- Experience working with structured, semi-structured, and unstructured data
- Hands-on expertise in containerization and orchestration using Docker and Kubernetes for scalable production systems
- Familiarity with distributed computing frameworks such as Spark and Dask
- Familiarity with cloud platforms such as AWS, Azure, and GCP
- Familiarity with analytics libraries such as pandas, numpy, and matplotlib
- Exposure to DevOps, DataOps, and MLOps concepts and best practices
- Experience with core technologies such as Python, PySpark, SQL, Airflow, Databricks, Kedro, Dask/RAPIDS, Docker, Kubernetes, and cloud services (AWS/GCP/Azure)
- Demonstrated experience working collaboratively with developers and technical and non-technical people within software teams
- Experience working in Agile teams including active participation in sprint ceremonies
- Exceptional time management in a complex and largely autonomous work environment
- Strong communication skills in English and local office language(s) with ability to adjust style to different perspectives and seniority levels
- Experience in Scala or Java
- Experience with Generative AI or agentic systems including building Retrieval-Augmented Generation systems, implementing large language models, or integrating advanced AI frameworks
- Exposure to AI modeling frameworks such as TensorFlow, PyTorch, Keras, or Scikit-Learn
- Familiarity with AI Governance and Safety principles including Responsible AI practices, bias and hallucination testing, and LLM safety guardrails
- Continuous learning culture with structured programs and clear, actionable feedback
- A voice that matters with opportunities to make tangible impact and contribute innovative ideas
- Global community with colleagues across 65+ countries and over 100 nationalities
- World-class benefits including competitive salary based on location, experience, and skills
- Comprehensive benefits package enabling holistic well-being for employees and their families
Skills
- Agentic AI
- Agile
- AI
- Airflow
- Analytics
- AWS
- Azure
- Cloud
- Containerization
- Dask
- Data Engineering
- Data Pipelines
- Data Quality
- Databricks
- DevOps
- Distributed Computing
- Docker
- GCP
- Generative AI
- Java
- Keras
- Kubernetes
- LLM
- Machine Learning
- Matplotlib
- MLOps
- NumPy
- pandas
- PySpark
- Python
- PyTorch
- RAG
- Scala
- scikit-learn
- Spark
- SQL
- TensorFlow