Senior AI Solutions Engineer
New
I
INFOPLUS TECHNOLOGIESAI and machine learning
Workplace type: remote; Locations: Kraków, Krakow, Kraków, Country code: PLContractSenior
Salary1,200 - 1,300 PLN per day
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Job Details
- Required Skills
- DockerPythonSQLMachine LearningSnowflakedbtMLOps
Requirements
- Demonstrate strong Python programming skills and produce production-quality, well-structured code.
- Be proficient in SQL and have experience working with large-volume datasets in Spark and/or Snowflake.
- Use Python and Bash for scripting, automation, and tooling.
- Have expertise with Git and version control workflows, including branching, code review, and pull requests.
- Have hands-on experience building and deploying machine learning on large-scale production datasets.
- Understand regression, classification, clustering, ensemble methods, time-series forecasting, and optimization modeling.
- Apply feature engineering, backtesting, statistical analysis, sound validation splits, and leakage avoidance.
- Have experience with Snowflake architecture, advanced SQL, ingestion, performance tuning, security, and data modeling.
- Be familiar with dbt, experiment tracking and model versioning, and orchestration tools such as Airflow, Azure Data Factory, or Dagster.
- Have experience building LLM applications or agents, including RAG, prompt engineering, grounding, and output evaluation.
- Understand OCR, document parsing, and NLP for unstructured and semi-structured documents.
- Have experience with Azure AI and machine-learning services, Docker, and containerized deployment.
- Have hands-on DevOps/MLOps experience, including CI/CD and infrastructure as code with Terraform or Bicep.
- Understand production deployment strategies, automated testing, monitoring, and troubleshooting.
- Be able to own technical roadmaps and architecture decisions, review code, mentor junior engineers, and communicate technical concepts to business users.
Responsibilities
- Build and deploy machine-learning models on large-scale production datasets.
- Develop AI agents and LLM applications using Azure AI Foundry, Azure model endpoints, and orchestration frameworks.
- Develop RAG pipelines with chunking, vector embedding and indexing, and LLM response generation.
- Integrate LLMs and agents with SQL and Snowflake data, tools, external systems, and APIs.
- Build and maintain data pipelines, dbt models, and orchestration for data workloads.
- Deploy and scale ML and LLM workloads on Azure using containers and CI/CD pipelines.
- Manage model lifecycle tasks, including model versioning, retraining pipelines, and endpoint management.
- Monitor production services and models using Azure Monitor and Application Insights; track drift and prediction quality.
- Own technical roadmaps and architecture decisions, set engineering standards, and review code.
- Mentor junior engineers and collaborate with analytics, BI, and data science teams.
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