AI Solutions Engineer
Posted Updated
Summary
Designs and builds AI and analytics solutions for McKinsey clients: scalable data pipelines for ML/AI, secure data environments, and software products, while mentoring client teams. Core stack includes Python, PySpark, SQL, Airflow, Databricks, Docker, Kubernetes, and cloud platforms.
- Design and build innovative AI solutions combining software development and data engineering
- Collaborate with global technologists, data scientists, and industry experts to transform businesses through analytics and AI
- Develop scalable data pipelines for machine learning and AI applications
- Build maintainable, scalable, and secure software products and services
- Assess data landscapes and ensure data quality 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
- Mentor client teams on engineering best practices, user-centric design, and Agile values
- 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 with structured, semi-structured, and unstructured data
- Hands-on expertise in containerization and orchestration using Docker and Kubernetes
- Familiarity with distributed computing frameworks such as Spark or Dask
- Familiarity with cloud platforms such as AWS, Azure, or GCP
- Familiarity with analytics libraries such as pandas, numpy, matplotlib
- Exposure to DevOps, DataOps, and MLOps concepts and best practices
- Experience with core technologies including Python, PySpark, SQL, Airflow, Databricks, Kedro, Dask/RAPIDS, Docker, Kubernetes, and cloud services
- 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
- Demonstrated experience working collaboratively with developers and technical and non-technical team members
- Experience working in Agile teams including active participation in sprint ceremonies
- Exceptional time management in a complex and autonomous work environment
- Strong verbal and written communication skills in English and local office languages
- Experience in Scala or Java programming
- Experience with Generative AI or agentic systems including building Retrieval-Augmented Generation systems, implementing large language models, or integrating advanced AI frameworks
- Continuous learning culture with structured programs and actionable feedback
- Opportunity to have a voice that matters and make tangible impact
- Global community with colleagues across 65+ countries and over 100 nationalities
- Competitive salary based on location, experience, and skills
- Comprehensive benefits package for holistic well-being
Skills
- Agentic AI
- Agile
- AI
- Airflow
- Analytics
- AWS
- Azure
- Cloud
- Containerization
- Dask
- Data Engineering
- Data Pipelines
- Data Quality
- Databricks
- DataOps
- 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