Build AI agents and orchestration flows using Python to automate complex workflows
Facilitate migration of internal tools to an AI-driven solution with a focus on multi-step, context-aware processes
Implement complex AI workflows utilizing LangChain systems to connect LLMs with internal data
Develop tools to automate the creation and validation of internal specification files
Move into a broader data role, contributing to data pipelines and modeling post-migration
At least 5 years of commercial experience in ML, AI or/and Big Data
Solid understanding of distributed data processing concepts and core data engineering principles (ETL/ELT, data modeling)
Proven ability to build production-grade applications using Python and large language models (LLMs)
Experience designing AI agents and orchestration flows (e.g., using LangChain, LlamaIndex, etc.)
Experience implementing function calling, context management, and RAG patterns
Demonstrated skill in crafting and optimizing prompts for complex, multi-step tasks
At least an Upper-Intermediate level of English
PERSONAL PROFILE
Excellent communication and interpersonal skills with the ability to collaborate effectively with cross-functional teams and stakeholders
Strong problem-solving and decision-making skills with a focus on driving results and meeting deadlines
Self-motivated, adaptable, and eager to learn new technologies and frameworks
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Understand the required skills and qualifications, anticipate the questions you may be asked, and study well-prepared answers using our sample responses.
ML Engineer Q&A's