4+ years of Data Engineering experience with the last 1 year in building data processing pipelines
4+ years of production-ready Python development (microservices, APIs, etc.)
1+ year of experience with GenAI (LLMs, agents, RAGs, prompt engineering, MCP, spec-driven development)
2+ years of experience in production-ready ML-related code development
Requirements:
Design, deliver and scale GenAI solutions and practical implementations of LLM/ML/AI automation for scale and efficiency
Implement AI Agents and ML models into production and design, deliver, and manage industrialized data processing pipelines; establish MLOps/LLMOps frameworks
Define and implement best practices across the ML model lifecycle and ML/LLMOps operations; gather requirements, estimate work, and present solutions to clients; create technical documentation
Collaborate with Data Science teams and communicate results to internal and external stakeholders; stay current with modern ML techniques, tools, and architectures
Job description
The person we are looking for will become part of Data Science and AI Competency Center working in AI Engineering team. The key duties are:
Design, deliver and scale GenAI solutions
Practical and innovative implementations of LLM/ML/AI automation, for scale and efficiency
Working with Data Science teams to implement AI Agents and Machine Learning models into production
Design, delivery and management of industrialized processing pipelines
Implementing AI /MLOps/LLMOps frameworks and supporting Data Science teams in best practices
Gathering and applying knowledge on modern techniques, tools and frameworks in the area of ML Architecture and Operations
Defining and implementing best practices in ML models life cycle and ML operations/LLM operations
Gathering technical requirements & estimating planned work
Presenting solutions, concepts and results to internal and external clients
Creating technical documentation
At least 4+ years of Data engineering experience with last 1 year-experience in building Data processing
At least 4+ years of experience in production-ready Python code development (e.g., microservices, APIs, etc.)
At least 1+ years of experience with GenAI (various LLM models, agents, RAGs, prompt engineering, MCP, specification-driven-development)
At least 2+ years of experience in production-ready ML-related code development
Additionally for all levels:
Good understanding of ML/AI concepts: types of algorithms, machine learning frameworks, model efficiency metrics, model life-cycle, AI architectures
Good understanding of Cloud concepts and architectures, as well as working knowledge with selected cloud services, preferably Azure or GCP
Experience in designing and implementing data pipelines
Good communication skills
Ability to work in a team and support others
Taking responsibility for tasks and deliverables
Great problem-solving skills and critical thinking
Fluency in written and spoken English.
Nice to have skills & knowledge:
Experience with LangGraph, FastAPI, CosmoDB, Redis, SpyGlass, Kubernetes
Experience in designing, programming ML algorithms, and data processing pipelines using Python
Experience in at least one of following domains: Data Warehouse, Data Lake, Data Integration, Data Governance, Machine Learning, Deep Learning, MLOps
Practical experience in MLOps/LLMOps tools like AzureML/AzureAI (or GCP equivalents)
Practical experience with Databricks
Practical experience in Spark/PySpark and Hive within Big Data Platforms like Databricks, EMR or similar
Good understanding of CI/CD and DevOps concepts, and experience in working with selected tools (preferably GitHub Actions, GitLab, or Azure DevOps)
Experience in productizing ML solutions using technologies like Spark/Databricks or Docker/Kubernetes.
